Fatigue and functioning
in rheumatic diseases :
a biopsychological perspective
Cécile L. Overman
Creator of cover image: Mario Sánchez Nevado (http://aegis-strife.net)
Printing and cover layout: Ridderkerk BV, the Netherlands
ISBN : 978-90-393-6324-9
Copyright : Cécile L. Overman, 2015
Fatigue and functioning
in rheumatic diseases:
a biopsychological perspective
Vermoeidheid en functioneren bij reumatische aandoeningen:
een biopsychologisch perspectief
(met een samenvatting in het Nederlands)
Proefschrift
ter verkrijging van de graad van doctor aan de Universiteit Utrecht op
gezag van de rector magnificus, prof.dr. G.J. van der Zwaan, ingevolge
het besluit van het college voor promoties in het openbaar te verdedigen
op vrijdag 22 mei 2015 des middags te 4.15 uur
door
Cécile Leontine Overman
geboren op 31 mei 1981 te Amsterdam
Promotoren :
Prof. dr. R. Geenen
Prof. dr. J.W.J. Bijlsma
Copromotor :
Dr. E.R. Bossema
Dit proefschrift werd mede mogelijk gemaakt met financiële steun van
het Reumafonds.
CONTENTS
Chapter 1
General introduction
7
Section 1
Fatigue
Chapter 2
The prevalence of severe fatigue in rheumatic
25
diseases: an international study
Chapter 3
Fatigue
in
patients
with
systemic
lupus
39
erythematosus: the role of dehydroepiandrosterone
sulphate
Chapter 4
The association of fatigue and disease activity in
55
patients with rheumatoid arthritis: a latent growth
curve
model
analysis
of
between-subject
differences and within-subject changes
Section 2
Functioning
Chapter 5
Change
of
psychological
distress
and
physical
71
disability in patients with rheumatoid arthritis over
the last two decades
Chapter 6
Contribution of the subjective components of the
89
Disease Activity Score to the response to biological
treatment in rheumatoid arthritis
Chapter 7
The prospective association between psychological
distress
and
disease
activity
in
103
rheumatoid
arthritis: a multilevel regression analysis
Chapter 8
General discussion
121
Samenvatting (Dutch summary)
135
Dankwoord (Acknowledgements)
143
Curriculum Vitae
147
Publications
149
Chapter 1
General introduction
7
CHAPTER 1
INTRODUCTION
Rheumatic
diseases
comprise
more
than
100
different
medical
conditions with a broad array of clinical manifestations, but are generally
characterized by inflammation, damage and/or pain of the joints and
connective tissues.1,2 They include common forms such as rheumatoid
arthritis (RA), osteoarthritis, and fibromyalgia, and less common forms
such as systemic lupus erythematosus (SLE) and scleroderma. Overall,
women are more often affected and the incidence increases with age. 1-3
In the Netherlands, 18% of the adult population is estimated to have a
rheumatic disease.4
Rheumatic diseases have a profound negative impact on almost
every aspect of a patient’s life as well as on the direct environment and
society as a whole.5 Patients are hampered in their daily activities by
pain, physical disability,5-7 and fatigue,8,9 and also psychological distress
is more prevalent than in the general population.10-15
The primary treatment in rheumatic diseases mostly involves
pharmacological treatment of inflammation and pain. However, a
patient’s health is not determined by physiological processes alone, but
by a complex interplay between biological, psychological and social
factors.16,17
Previous
research
has
provided
associations and mutual impact of these factors,
insight
18-26
into
possible
but more research,
especially prospective research taking account of between-subject
differences and within-subject changes, is needed to clarify the
existence and nature of dynamic relations between physiological and
psychological processes in rheumatic diseases. This thesis focuses on
fatigue and on physical and psychological functioning by examining their
prevalence
and
possible
association
and
dynamic
interplay
with
biological factors in four longitudinal studies that take account of
between- and within-subject differences and two cross-sectional studies.
Figure 1 depicts the factors studied in this thesis and their possible
relationships.
8
GENERAL INTRODUCTION
Figure 1. Conceptual model of the interrelationships between physiological factors of
rheumatic disease, fatigue and functioning that are studied in this thesis
FATIGUE
As one of the most prevalent and debilitating symptoms,27-34 fatigue is
an important burden of rheumatic disease. Fatigue restricts patients’
abilities to work and engage in social and leisure activities.35,36 In SLE it
is considered the most disabling and enduring complaint even when
disease activity is low.31,37,38 Patients with RA describe fatigue as
different
from
normal
tiredness
by
being
overwhelming
and
disproportionate or unrelated to activity, and affecting every sphere of
life.35,39
In recent years, the importance of fatigue in rheumatic diseases
has been acknowledged by the scientific and medical community with
fatigue now being recognized as a core symptom and outcome measure
in RA, psoriatic arthritis, ankylosing spondylitis, and fibromyalgia.39-42
However, although fatigue is recognized as important by both patients
and doctors, it is still often ignored in clinical practice and patients
struggle to self-manage it.35,36,43 Effective treatment of fatigue has been
hampered by the unknown pathology of fatigue43-45 with possibly
multiple biological and psychological factors triggering and maintaining
fatigue.9 The complexity of fatigue with its subjective nature and
physical and psychological aspects has led to many different definitions46
and measures of fatigue43,44 and inconsistencies between studies on the
9
CHAPTER 1
prevalence of fatigue in rheumatic diseases.43 Chapter 2 of this thesis
aims to clarify clinically relevant fatigue across a broad range of
rheumatic diseases by examining the prevalence of severe fatigue
comparable to the level of fatigue in patients with chronic fatigue
syndrome.
The hormones involved in energy expenditure may play a role in
the persistence of fatigue in rheumatic diseases.44,47 Inflammation
appeals to the endocrine system, which may have consequences for
common levels of hormones. Especially androgens have been related to
fatigue and vitality.48 Decreased levels of testosterone have been
associated
with
low
physical
and
cognitive
vitality.49
Dehydroepiandrosterone (DHEA) and its sulphate ester DHEAS are
androgens secreted in abundance by the human adrenal glands in
response to activity of the hypothalamic-pituitary adrenal axis (HPAaxis) and are natural precursors of estrogen and testosterone. With age,
DHEA(S) levels progressively decline and DHEA has been advertised as
a supplement to, among other anti-aging benefits, boost energy
levels.23,49 Studies on the administration of DHEA in elderly people and
some patient populations with low serum DHEA levels reported
improvements in psychological well-being and fatigue.48,50-56 In some
rheumatic diseases such as SLE, serum levels of DHEA(S) are low
compared to healthy subjects23,57,58 The existence of both low serum
DHEA(S) levels and high levels of fatigue in SLE and the reported
correlations between DHEA(S) levels and well-being in various groups
motivated the study described in chapter 3 in which the possible
association between DHEA(S) and fatigue in rheumatic disease is
examined in women with SLE.
Fatigue is common, not only in rheumatic diseases, but in all
chronic diseases.59 The idea that disease is somehow a precipitating
factor of fatigue seems therefore obvious and both patients with RA and
doctors indeed ascribe fatigue to inflammatory activity.35,60-62 Rheumatic
inflammatory processes could induce fatigue as part of a constellation of
non-specific symptoms called “sickness behaviour”, which is considered
a natural homeostatic reaction aimed at recovery.18 Other symptoms of
sickness behaviour include depressed mood, anxiety, impaired cognitive
ability, loss of appetite, loss of libido, psychomotor slowing, sleep
10
GENERAL INTRODUCTION
disturbances and increased sensitivity to pain.18,19 Both animal research
and effects of immunotherapy in humans indicate that pro-inflammatory
cytokines, which also play an important role in inflammation, mediate
these symptoms of sickness behavior.20-22,63,64 However, although
research indicates a relation between inflammation and fatigue, in
rheumatic
diseases
such
as
RA
and
SLE
correlations
between
inflammatory markers and fatigue are mostly absent or small.27-29,6569,31,38
Still, studies so far particularly examined the between-subject
association of disease activity and fatigue rather than the within-subject
association between fluctuations of disease activity and fatigue. The
association of within-subject changes in disease activity and fatigue
might be hidden by the between-subject differences in level. Unravelling
between- and within-subject associations might show that within
patients, changes in disease activity are related to changes in fatigue
while between patients, levels of disease activity and fatigue are
unrelated. In chapter 4 of this thesis, a latent growth curve model is
used to examine simultaneously the association between both betweensubject levels and within-subject changes of objective indicators of
disease activity and fatigue.
PHYSICAL AND PSYCHOLOGICAL FUNCTIONING
Patients with a rheumatic disease often
have impaired physical
functioning partly due to pain, fatigue, tissue damage and deformity.5-7
This loss of function may, together with other factors such as circadian
rhythm disturbance, loss of valued activities across multiple life
domains, and the unpredictable and sometimes uncontrollable course of
the disease lead to psychological distress.14,70-72 Indeed, in patients with
a rheumatic disease, percentages of depressed mood and anxiety are
overall
approximately
population.
twice
as
high
as
in
the
general
10,11,13,14,70,73-79
For the treatment of RA, new and improved strategies have
emerged,71,80-91 which may have led to better physical functioning and
may have alleviated some of the psychological distress, partly by better
controlling disease activity and deterioration. At the same time, more
attention to the overall well-being of patients, treatment of psychological
distress, and improved self-regulation education may have positively
11
CHAPTER 1
influenced health behaviours (e.g. physical exercise, doctor visits,
adherence, sleep hygiene, smoking) which may have improved disease
outcome.17 Improved psychological well-being and physical functioning
have
been
associated
81,82,85,91,92
trials.
with
new
treatment
strategies
in
clinical
So far, population studies did not examine improvement
in both psychological distress and physical functioning in multiple
consecutive cohorts, over a long time period extending to recent
years.93-97 Due to our possession of a unique and homogeneous dataset
of cohorts of patients who all had a recent RA diagnosis, we had the
opportunity to examine the change in psychological distress and physical
disability and the possible association with a change in disease activity
over the last 20 years in consecutive cohorts of patients with RA, both at
diagnosis and after four years of treatment. Chapter 5 describes this
study.
Perhaps the most significant improvement of treatment of RA in
the past decades has been the introduction of biologicals that inhibit the
activity of pro-inflammatory cytokines.86,88 Still, in about 50% of
patients, biologicals are not effective.98 To decide on starting treatment
with biologicals, the Disease Activity Score based on 28 joints (DAS28)
is most commonly used.99 It comprises two objective physiological
markers, erythrocyte sedimentation rate and swollen joint count, and
two subjective (psychologically influenced), patient-reported outcomes,
the visual analogue scale of general well-being and the tender joint
count. Studies indicate that in RA, psychological distress is associated
with a poor long-term outcome100-102 and that high physical disability
and pain may lead to over-interpretation of active disease when
assessed by a summative measure like the DAS28.103 This could imply
that biologicals are sometimes prescribed unjustly to patients who
perceive a high subjective burden of the disease with relatively low
inflammatory activity and damage. Therefore, we hypothesized that
patients with high scores on the subjective components of the DAS28,
relative to the objective components, may have a lower response to
biological treatment than patients with lower scores on these subjective
components. Chapter 6 examines whether a lack of response to
biological treatment can be partly attributable to high scores on the
subjective, patient-reported components of the DAS28.
12
GENERAL INTRODUCTION
Depressed mood and anxiety may, just as fatigue, be influenced
by activation of pro-inflammatory cytokines during disease flare-ups.1822,63,64
However, cytokine activation may not only affect psychological
distress, it has been proposed that psychological distress also affects
cytokine activation. Psychological distress may increase production of
pro-inflammatory cytokines by causing enduring overactivation of the
stress axes (i.e. HPA-axis and sympathetic-adrenal-medullary axis).24-26
Prolonged overactivation of these stress axes (due to psychological
distress, inflammation, or other causes) may cause the immune system
to become desensitized to the inhibitory hormonal output of these axes
which may boost the production of pro-inflammatory cytokines.104-107
Patients with RA often attribute their disease flares to psychological
stress,108,109 but the reciprocal association between psychological status
and disease status in patients with RA was not yet examined in a
prospective study using multiple repeated measurements. Chapter 7
presents the first prospective study of the possible mutual impact of
psychological distress and disease activity in patients with RA.
THESIS OUTLINE AND AIMS
This thesis comprises two sections: the first section focuses on fatigue
and its possible association with disease activity, the second section
focuses on physical and (foremost) psychological functioning and the
interplay of these factors with disease activity.
Fatigue
Chapter 2: Given the lack of clarity about the prevalence of severe clinically relevant - fatigue in rheumatic diseases, this chapter examines
the percentages of patients with severe fatigue across a broad range of
rheumatic diseases using a uniform measure of fatigue and a stringent
cut-off criterion indicating a level of fatigue that is comparable with
fatigue in patients with chronic fatigue syndrome. Moreover, the
association of severe fatigue with having (comorbid) fibromyalgia,
having multiple rheumatic diseases not including fibromyalgia, and
demographic variables is examined.
Chapter 3: DHEA(S) has been associated with well-being and is said to
enhance vitality when given as a supplement. Low mean DHEA(S) levels
13
CHAPTER 1
in some rheumatic diseases may play a role in fatigue. This chapter
reports the association between endogenous levels of DHEA(S) and
fatigue in women with SLE.
Chapter 4: This chapter clarifies and unravels the association between
disease activity and fatigue. It is hypothesized that individual differences
in levels of disease activity and RA fatigue hide an association between
fluctuations in disease activity and fatigue. The association of betweensubject differences and within-subject changes of objective indicators of
disease activity and fatigue as well as the association of patient
characteristics with between-subject differences and within-subject
changes in fatigue are examined across six months in patients with RA
undergoing biological treatment.
Functioning
Chapter 5: The enhanced focus on improving well-being and functioning
and the improved pharmacotherapy may have resulted in a reduction of
psychological distress and physical disability. We used a unique dataset
to examine whether psychological distress and physical disability
decreased over the last two decades in patients with a recent RA
diagnosis and whether this decrease was associated with a parallel
reduction of disease activity.
Chapter 6: A substantial proportion of patients with RA do not respond
satisfactorily to treatment with biological inhibitors of pro-inflammatory
cytokines. This lack of response to treatment might particularly be
prominent in patients scoring high on the patient-reported (subjective)
components of the DAS28 relative to the inflammatory (objective)
components. This chapter examines whether patients with RA who do
not respond well to biological treatment have relatively high subjective
DAS28 scores at baseline and after three months.
Chapter 7: An association between psychological distress and disease
activity has long been assumed but not been thoroughly examined in a
prospective multilevel study including multiple repeated measurements.
This chapter examines both the concurrent and prospective associations
between psychological distress and disease activity in patients with a
recent diagnosis of RA, followed during five years.
14
GENERAL INTRODUCTION
General discussion
Chapter 8: The final chapter discusses the main findings of this thesis
and presents clinical implications and future directions.
REFERENCES
1.
Silman AJ, Hochberg MC. Epidemiology of the rheumatic diseases. New York:
Oxford University Press, 1993.
2.
Sangha O. Epidemiology of rheumatic diseases. Rheumatology 2000;39 Suppl 2:312.
3.
Gabriel SE, Michaud K. Epidemiological studies in incidence, prevalence, mortality,
and comorbidity of the rheumatic diseases. Arthritis Res Ther 2009;11:229.
4.
Chorus AMJ, Schokker DF. Nationale peiling bewegingsapparaat 2010. Het
Reumafonds. TNO, 2011.
5.
Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health
Organ 2003;81:646-56.
6.
Tench C, Bentley D, Vleck V, McCurdie I, White P, D’Cruz D. Aerobic fitness,
fatigue, and physical disability in systemic lupus erythematosus. J Rheumatol
2002;29:474-81.
7.
Strömbeck B, Ekdahl C, Manthorpe R, Jacobsson LT. Physical capacity in women
with
primary
Sjögren’s
syndrome:
a
controlled
study.
Arthritis
Rheum
2003;49:681-8.
8.
Hewlett S, Nicklin J, Treharne GJ. Fatigue in musculoskeletal conditions. Arthritis
Res UK Top Rev 2008;6:1.
9.
Stebbings S, Treharne GJ. Fatigue in rheumatic disease: an overview. Int J Clin
Rheumatol 2010;5:487–502.
10.
Geenen R, Newman S, Bossema ER, Vriezekolk JE, Boelen PA. Psychological
interventions for patients with rheumatic diseases and anxiety or depression. Best
Pract Res Clin Rheumatol 2012;26:305-19.
11.
Dickens C, McGowan L, Clark-Carter D, et al. Depression in rheumatoid arthritis: A
systematic
review
of
the
literature
with
meta-analysis.
Psychosom
Med
2002;64:52-60.
12.
Vandyke MM, Parker JC, Smarr KL, et al. Anxiety in rheumatoid arthritis. Arthritis
Rheum 2004;51:408-12.
13.
Isik A, Koca SS, Ozturk A, et al. Anxiety and depression in patients with rheumatoid
arthritis. Clin Rheumatol 2007;26:872-8.
14.
Bachen EA, Chesney MA, Criswell LA. Women with systemic lupus erythematosus.
Arthritis Rheum 2009;61:822-9.
15.
Valtýsdóttir ST, Gudbjörnsson B, Lindqvist U, Hällgren R, Hetta J. Anxiety and
depression
in
patients
with
primary
Sjögren’s
syndrome.
J
Rheumatol
2000;27:165-9.
16.
Engel GL. The need for a new medical model: a challenge for biomedicine. Science
1977;196:129-36.
15
CHAPTER 1
17.
Geenen R, Finset A. Psycho-social approaches in rheumatic diseases. In: Bijlsma
JWJ, Da Siva JAP, Hachulla E, Doherty M, Cope A, Lioté F (Eds). EULAR textbook on
rheumatic diseases. London: BMJ Group 2012:139-62.
18.
Dantzer R. Cytokine-induced sickness behavior: where do we stand? Brain Behav
Immun 2001;15:7–24.
19.
Maier SF, Watkins LR. Cytokines for psychologists: implications of bidirectional
immune-to-brain communication for understanding behavior, mood, and cognition.
Psychol Rev 1998;105:83-107.
20.
Anisman H, Merali Z. Anhedonic and anxiogenic effects of cytokine exposure. Adv
Exp Med Biol. 1999;461:199-233.
21.
Yirmiya R. Endotoxin produces a depressive-like episode in rats. Brain Res
1996;711:163-74.
22.
Capuron L, Miller AH. Cytokines and psychopathology: Lessons from interferon-α.
Biol Psychiatry 2004;56:819-24.
23.
Derksen
RHWM.
Dehydroepiandrosterone
(DHEA)
and
systemic
lupus
erythematosus. Semin Arthritis Rheum 1998;27:335-47.
24.
Barden
N.
Implication
of
the
hypothalamic-pituitary-adrenal
axis
in
the
physiopathology of depression. J Psychiatry Neurosci 2004; 29:185-93.
25.
Claes SJ. CRH, Stress, and Major Depression: A Psychobiological Interplay. Vitam
Horm 2004;69:117-50.
26.
Pariante
CM.
Depression,
stress
and
the
adrenal
axis.
J
Neuroendocrinol
2003;15:811-2.
27.
Wolfe F, Hawley DJ, Wilson K. The prevalence and meaning of fatigue in rheumatic
disease. J Rheumatol 1996;23:1407-1417.
28.
Van Hoogmoed D, Fransen J, Bleijenberg G, van Riel P. Physical and psychosocial
correlates of severe fatigue in rheumatoid arthritis. Rheumatology 2010;49:1294–
1302.
29.
Pollard LC, Choy EH, Gonzalez J, Khoshaba B, Scott DL. Fatigue in rheumatoid
arthritis reflects pain, not disease activity. Rheumatology (Oxford) 2006;45:885-9.
30.
Cleanthous S, Tyagi M, Isenberg DA, Newman SP. What do we know about selfreported fatigue in systemic lupus erythematosus? Lupus 2012;21:465-76.
31.
Tench CM, McCurdie I, White PD, D'Cruz DP. The prevalence and associations of
fatigue in systemic lupus erythematosus. Rheumatology 2000;39:1249-1254.
32.
Segal B, Thomas W, Rogers T, et al. Prevalence, severity, and predictors of fatigue
in subjects with primary Sjögren's syndrome. Arthritis Rheum. 2008;59:1780-1787.
33.
Barendregt PJ, Visser MR, Smets EM, et al. Fatigue in primary Sjögren's syndrome.
Ann Rheum Dis 1998;57:291-295.
34.
Sandusky SB, McGuire L, Smith MT, Wigley FM, Haythornthwaite JA. Fatigue: an
overlooked
determinant
of
physical
function
in
scleroderma.
Rheumatology
2009;48:165-169.
35.
Hewlett S, Cockshott Z, Byron M, et al. Patients’ perceptions of fatigue in
rheumatoid arthritis: overwhelming, uncontrollable, ignored. Arthritis Rheum
2005;53:697-702.
36.
Power JD, Badley EM, French MR, Wall AJ, Hawker GA. Fatigue in osteoarthritis: a
qualitative study. BMC Musculoskelet Disord 2008;9:63.
16
GENERAL INTRODUCTION
37.
Bruce IN, Mak VC, Hallett DC, Gladman DD, Urowitz MB. Factors associated with
fatigue
in
patients
with
systemic
lupus
erythematosus.
Ann
Rheum
Dis
1999;58:379-81.
38.
Wang B, Gladman DD, Urowitz MB. Fatigue in lupus is not correlated with disease
activity. J Rheumatol 1998;25:892-5.
39.
Kirwan J, Minnock P, Adebajo A, et al. Patient perspective: fatigue as a
recommended patient centered outcome measure in rheumatoid arthritis. J
Rheumatol 2007;34:1174-7.
40.
Husted JA, Tom BD, Schentag CT, Farewell VT, Gladman DD. Occurrence and
correlates of fatigue in psoriatic arthritis. Ann Rheum Dis 2009;68:1553-8.
41.
Van Tubergen A, Coenen J, Landewé R, et al. Assessment of fatigue in patients with
ankylosing spondylitis: a psychometric analysis. Arthritis Rheum 2002;47:8-16.
42.
Wolfe F, Clauw DJ, Fitzcharles MA, et al. The American College of Rheumatology
preliminary diagnostic criteria for fibromyalgia and measurement of symptom
severity. Arthritis Care Res 2010;62:600-10.
43.
Repping-Wuts H, van Riel P, van Achterberg T. Rheumatologists' knowledge,
attitude
and
current
management
of
fatigue
in
patients
with
rheumatoid
arthritis(RA). Clin Rheumatol 2008;27:1549-1555.
44.
Dupond JL. Fatigue in patients with rheumatic diseases. Joint Bone Spine
2011;78:156-160.
45.
Hewlett S, Hehir M, Kirwan JR. Measuring fatigue in rheumatoid arthritis: a
systematic review of scales in use. Arthritis Car Res 2007;57:429-39.
46.
Aaronson LS, Teel CS, Cassmeyer V, et al. Defining and measuring fatigue. J Nurs
Schol 1999;31:45-50.
47.
Dekkers JC, Geenen R, Godaert GL, van Doornen LJ, Bijlsma JWJ. Diurnal rhythm of
salivary cortisol levels in patients with recent-onset rheumatoid arthritis. Arthritis
Rheum 2000;43:465-7.
48.
Hunt PJ, Gurnell EM, Huppert FA, et al. Improvement in mood and fatigue after
dehydroepiandrosterone replacement in Addison's disease in a randomized, double
blind trial. J Clin Endocrinol Metab 2000; 85:4650-6.
49.
Fillit HM, Butler RN, O’Connell AW, et al. Achieving and maintaining cognitive
vitality with aging. Mayo Clin Proc 2002;77:681-96.
50.
Morales AJ, Nolan JJ, Nelson JC, Yen SSC. Effects of Replacement Dose of
Dehydroepiandrosterone in Men and Women of Advancing Age. J Clin Endocrinol
Metab 1994; 78: 1360-1367.
51.
Casson PR, Faquin LC, Stentz FB, et al. Replacement of dehydroepiandrosterone
enhances T-lymphocyte insulin binding in postmenopausal women. Fertil Steril
1995; 63:1027-1031.
52.
Yen SS, Morales AJ, Khorram O. Replacement of DHEA in aging men and women.
Potential remedial effects. Ann NY Acad Sci 1995; 774: 128-142.
53.
Himmel PB, Seligman TM. A pilot study employing dehydroepiandrosterone (DHEA)
in the treatment of chronic fatigue syndrome. J Clin Rheumatology 1999; 5: 56-59.
54.
Wolkowitz OM, Reus VI, Keebler A, et al. Double-blind treatment of major
depression with dehydroepiandrosterone. Am J Psychiatry 1999; 156: 646-649.
17
CHAPTER 1
55.
Johannsson G, Burman P, Wiren L, et al. Low dose dehydroepiandrosterone affects
behavior in hypopituitary androgen-deficient women: a placebo-controlled trial. J
Clin Endocrinol.Metab 2002; 87: 2046-2052.
56.
Arlt W, Callies F, van Vlijmen JC, et al. Dehydroepiandrosterone replacement in
women with adrenal insufficiency. N Engl J Med 1999; 341: 1013-1020.
57.
Hedman M, Nilsson E, De la Torre B. Low sulpho-conjugated steroid hormone levels
in systemic lupus erythematosus (SLE). Clin Exp Rheumatol 1989; 7:583-8.
58.
Lahita RG, Bradlow HL, Ginzler E. Low plasma androgens in women with systemic
lupus erythematosus. Arthritis Rheum 1987; 30:241-8.
59.
Swain MG. Fatigue in chronic disease. Clin Sci 2000;99:1-8.
60.
Crosby LJ. Factors which contribute to fatigue associated with rheumatoid arthritis.
J Adv Nurs 1991;16:974-81.
61.
Repping-Wuts JWJ, Fransen J, van Achterberg T, Bleijenberg G, van Riel P.
Persistent severe fatigue in patients with Rheumatoid Arthritis. J Clin Nurs
2007;16:377-83.
62.
Rasker JJ. The enigma of fatigue. J Rheumatol 2009;36:2630-2.
63.
Capuron L, Gumnick JF, Musselman DL, et al. Neurobehavioral effects of interferonα in cancer patients: Phenomenology and paroxetine responsiveness of symptom
dimensions. Neuropsychopharmacology 2002;26:643-52.
64.
Meyers CA. Mood and cognitive disorders in cancer patients receiving cytokine
therapy. Adv Exp Med Biol. 1999;461:75-81.
65.
Bergman MJ, Shahouri SS, Shaver TS, et al. Is fatigue an inflammatory variable in
rheumatoid
arthritis
(RA)?
Analyses
of
fatigue
in
RA,
osteoarthritis,
and
fibromyalgia. J Rheumatol 2009;36:2788-94.
66.
Stebbings S, Herbison P, Doyle TC, Treharne GJ, Highton J. A comparison of fatigue
correlates in rheumatoid arthritis and osteoarthritis: disparity in associations with
disability, anxiety and sleep disturbance. Rheumatology (Oxford) 2010;49:361–7.
67.
Campbell RCJ, Batley M, Hammond A, Fowiza I, Kingsley G, Scott DL. The impact of
disease
activity, pain,
disability
and
treatments
on fatigue
in
established
rheumatoid arthritis. Clin Rheumatol 2012;31:717-22.
68.
Minnock P, McKee G, Bresnihan B, FitzGerald O, Veale DJ. How much is fatigue
explained by standard clinical characteristics of disease activity in patients with
inflammatory arthritis? A longitudinal study. Arthritis Car Res 2014;66:1597-1603.
69.
Burgos PI, Alarcón GS, McGwin Jr. G, Crews KQ, Reveille JD, Vilá LM. Disease
activity and damage are not associated with increased levels of fatigue in systemic
lupus erythematosus patients from a multiethnic cohort: LXVII. Arthritis Rheum
2009; 61:1179-86.
70.
Margaretten M, Yelin E, Imboden J, et al. Predictors of depression in a multiethnic
cohort of patients with rheumatoid arthritis. Arthritis Rheum 2009;61:1586-91.
71.
Geenen R, Mulligan K, Shipley M, Newman S. Psychosocial dimensions of the
rheumatic diseases. In: Bijlsma JWJ, Da Silva J, Faarvang KL, Burmeister G,
Hachulla E, Mariette X, eds. EULAR Compendium on Rheumatic Diseases. London:
BMJ Publishing Group 2009:637-50.
18
GENERAL INTRODUCTION
72.
Evers AWM, Kraaimaat FW, Geenen R, et al. Determinants of psychological distress
and its course in the first year after diagnosis in rheumatoid arthritis patients. J
Behav Med 1997;20:489-504.
73.
Abdel-Nasser AM, Abd El-Azim S, Taal E, et al. Depression and depressive
symptoms in rheumatoid arthritis patients: An analysis of their occurrence and
determinants. Br J Rheumatol 1998;37:391-7.
74.
Creed F. Psychological disorders in rheumatoid arthritis: A growing consensus? Ann
Rheum Dis 1990;49:808-12.
75.
Pincus T, Griffith J, Pearce S, et al. Prevalence of self-reported depression in
patients with rheumatoid arthritis. Br J Rheumatol 1996;35:879-83.
76.
Smedstad LM, Moum T, Vaglum P, et al. The Impact of Early Rheumatoid Arthritis
on Psychological Distress: A comparison between 238 patients with RA and 116
matched controls. Scand J Rheumatol 1996;25:377-82.
77.
Covic T, Tyson G, Spencer D, et al. Depression in rheumatoid arthritis patients:
demographic, clinical, and psychological predictors. J Psychosom Res 2006;60:46976.
78.
Frank RG, Beck NC, Parker JC, et al. Depression in rheumatoid arthritis. J
Rheumatol 1988;15:920-5.
79.
Wiltink J, Beutel ME, Till Y, et al. Prevalence of distress, Comorbid conditions and
well being in the general population. J Affective Disord 2011;130:429-37.
80.
Van der Heide A, Jacobs JWG, Bijlsma JWJ, et al. The Effectiveness of Early
Treatment with “Second-Line” Antirheumatic Drugs: A Randomized, Controlled
Trial. Ann Intern Med 1996;124:699-707.
81.
Verstappen SMM, Jacobs JWG, Bijlsma JWJ, et al. Five-year follow-up of rheumatoid
arthritis patients after early treatment with disease-modifying antirheumatic drugs
versus treatment according to the pyramid approach in the first year. Arthritis
Rheum 2003;48:1797–1807.
82.
Verstappen SMM, Jacobs JWG, Van der Veen MJ, et al. Intensive treatment with
methotrexate in early rheumatoid arthritis: aiming for remission. Computer
Assisted Management in Early Rheumatoid Arthritis (CAMERA, an open-label
strategy trial). Ann Rheum Dis 2007;66:1443-9.
83.
Jurgens MS, Welsing PMJ, Jacobs JWG. Overview and analysis of treat-to-target
trials
in
rheumatoid
arthritis
reporting
on
remission.
Clin
Exp
Rheumatol 2012;30:S56-63.
84.
Boers M, Verhoeven AC, Markusse HM, et al. Randomised comparison of combined
step-down prednisolone, methotrexate and sulphasalazine with sulphasalazine
alone in early rheumatoid arthritis. Lancet 1997;350:309-18.
85.
Bakker MF, Jacobs JWG, Welsing PMJ, et al. Low-dose prednisone inclusion in a
methotrexate-based, tight control strategy for early rheumatoid arthritis: a
randomized trial. Ann Intern Med 2012;156:329-39.
86.
Furst D, Breedveld F, Kalden J, et al. Updated consensus statement on biological
agents,
specifically
tumour
necrosis
factor
α
(TNFα) blocking
agents
and
interleukin-1 receptor antagonist (IL-1ra), for the treatment of rheumatic diseases,
2005. Ann Rheum Dis 2005;64:iv2–iv14.
19
CHAPTER 1
87.
Smolen JS, Boers M, Abadie EC, et al. Recommendations for an update of 2003
European regulatory requirements for registration of drugs to be used in the
treatment of RA. Curr Med Res Opin 2011;27:315-25.
88.
Jung YO, Kim HA. Recent Paradigm Shifts in the Diagnosis and Treatment of
Rheumatoid Arthritis. Korean J Intern Med 2012;27:378-87.
89.
Sharma P, Pathak K. Are biological targets the final goal for rheumatoid arthritis
therapy? Expert Opin Biol Ther 2012;12:1611-22.
90.
De Ridder D, Geenen R, Kuijer R, Van Middendorp H. Psychological adjustment to
chronic disease. Lancet 2008;372:246–55.
91.
De Jong Z, Munneke M, Zwinderman AH, et al. Is a long-term high-intensity
exercise program effective and safe in patients with rheumatoid arthritis? Results of
a randomized controlled trial. Arthritis Rheum 2003;48:2415–24.
92.
Singh JA, Christensen R, Wells GA, et al. A network meta-analysis of randomized
controlled trials of biologics for rheumatoid arthritis: A Cochrane overview.
CMAJ 2009;181:787-96.
93.
Pincus T, Sokka T, Kautiainen H. Patients seen for standard rheumatoid arthritis
care have significantly better articular, radiographic, laboratory, and functional
status in 2000 than in 1985. Arthritis Rheum 2005;52:1009–19.
94.
Heiberg T, Kvien TK, Uhlig T, FA. Seven year changes in health status and priorities
for improvement of health in patients with rheumatoid arthritis. Ann Rheum Dis
2005;64:191–5.
95.
Söderlin MK, Lindroth Y, Jacobsson LTH. Trends in medication and health-related
quality of life in a population-based rheumatoid arthritis register in Malmö, Sweden.
Rheumatology (Oxford) 2007;46:1355–8.
96.
Uhlig T, Heiberg T, Mowinckel P, Kvien TK. Rheumatoid arthritis is milder in the new
millennium:
health
status
in
RA
patients
1994–2004.
Ann
Rheum
Dis
2008;67:1710–5.
97.
Söderlin MK, Lindroth Y, Turesson C, Jacobsson LTH. A more active treatment has
profound effects on the health status of rheumatoid arthritis (RA) patients: results
from a population-based RA register in Malmö, Sweden, 1997–2005. Scand J
Rheumatol 2010;39:206–11.
98.
Olsen NJ, Stein CM. New drugs for rheumatoid arthritis. N Engl J Med
2004;350:2167-79.
99.
Prevoo ML, van 't Hof MA, Kuper HH, van Leeuwen MA, van de Putte LB, van Riel
PL. Modified disease activity scores that include twenty-eight-joint counts.
Development and validation in a prospective longitudinal study of patients with
rheumatoid arthritis. Arthritis Rheum 1995;38:44-8.
100.
Ødegård S, Finset A, Mowinckel P,et al. Pain and psychological health status over a
10-year period in patients with recent onset rheumatoid arthritis. Ann Rheum Dis
2007;66:1195-201.
101.
Evers AWM, Kraaimaat FW, Geenen R, Jacobs JWG, Bijlsma JWJ. Longterm
predictors of anxiety and depressed mood in early rheumatoid arthritis: a 3 and 5
year follow-up. J Rheumatol 2002;29:2327-36.
20
GENERAL INTRODUCTION
102.
Morris A, Yelin EH, Panopalis P, Julian L, Katz PP. Long-term patterns of depression
and associations with health and function in a panel study of rheumatoid arthritis. J
Health Psychol 2011;16:667-77.
103.
Pollard LC, Kingsley GH, Choy EH, Scott DL. Fibromyalgic rheumatoid arthritis and
disease assessment. Rheumatology (Oxford) 2010;49:924-8.
104.
Miller GE, Cohen S, Ritchey AK. Chronic psychological stress and the regulation of
pro-inflammatory cytokines: A glucocorticoid-resistance model. Health Psychol
2002;21:531-41.
105.
Zhou D, Kusnecov AW, Shurin MR, et al. Exposure to physical and psychological
stressors
elevates
plasma interleukin
6:
Relationship
to
the
activation
of
hypothalamic-pituitary- adrenal axis. Endocrinology 1993;133:2523-30.
106.
Pace TWW, Hu F, Miller AH. Cytokine-effects on glucocorticoid receptor function:
Relevance to glucocorticoid resistance and the pathophysiology and treatment of
major depression. Brain Behav Immun 2007;21:9-19.
107.
Raison CL, Miller AH. When not enough is too much: The role of insufficient
glucocorticoid signaling in the pathophysiology of stress-related disorders. Am J
Psychiatry 2003;160:1554-65.
108.
Geenen R, Van Middendorp H, Bijlsma JWJ. The impact of stressors on health status
and
hypothalamic-pituitary-adrenal
axis
and
autonomic
nervous
system
responsiveness in rheumatoid arthritis. Ann NY Acad Sci 2006;1069:77-97.
109.
Affleck G, Pfeiffer C, Tennen H, Fifield J. Attributional processes in rheumatoid
arthritis patients. Arthritis Rheum 1987;30:927-31.
21
22
Section 1
Fatigue
23
24
Chapter 2
The prevalence of severe fatigue
in rheumatic diseases: an
international study
Cécile L. Overman
Marianne B. Kool
José A.P. Da Silva
Rinie Geenen
Submitted as:
Overman, C.L., Kool, M.B., Da Silva, J.A.P., Geenen, R. The prevalence
of severe fatigue in rheumatic diseases: an international study.
25
CHAPTER 2
ABSTRACT
Background: Fatigue is a common, disabling, and difficult to manage
problem in rheumatic diseases. Prevalence estimates of fatigue within
rheumatic diseases vary considerably. Data on the prevalence of severe
fatigue across multiple rheumatic diseases using a similar instrument is
missing.
Objective: To provide an overview of the prevalence of severe fatigue
across a broad range of rheumatic diseases and to examine its
association with clinical and demographic variables.
Methods: Online questionnaires were filled out by an international
sample of 6120 patients (88% female, mean age 47) encompassing 30
different rheumatic diseases. Fatigue was measured with the RAND(SF)36 Vitality scale. A score of ≤ 35 was taken as representing severe
fatigue (90% sensitivity and 81%
specificity for chronic fatigue
syndrome).
Results: Severe fatigue was present in 41% to 57% of patients with a
single inflammatory rheumatic disease such as rheumatoid arthritis,
systemic
lupus
erythematosus,
ankylosing
spondylitis,
Sjögren’s
syndrome, psoriatic arthritis and scleroderma. Severe fatigue was least
prevalent in patients with osteoarthritis (35%) and most prevalent in
patients with fibromyalgia (82%). In logistic regression analysis, severe
fatigue was predicted by having fibromyalgia, having multiple rheumatic
diseases without fibromyalgia, younger age, lower education, and
linguistic
background
(French:
highest
prevalence;
Dutch:
lowest
prevalence).
Conclusion: One out of every two patients with a rheumatic disease is
severely fatigued. As severe fatigue is detrimental to the patient, the
near environment and society at large, unravelling the underlying
mechanisms of fatigue and developing optimal treatment should be top
priorities in rheumatologic research and practice.
26
PREVALENCE OF SEVERE FATIGUE
INTRODUCTION
Fatigue is a common problem in patients with a rheumatic disease. It
can be as disabling as pain, is difficult to manage and has a substantial
impact on quality of life.1-10 Due to its subjective nature, lack of
consensus on its definition, and the use of different measures to assess
fatigue,4,11 it is difficult to determine how widespread severe fatigue
really is among patients with rheumatic diseases. Indeed, prevalence
estimates of fatigue vary considerably within rheumatic diseases4 and
the evaluation of the prevalence of severe fatigue with a uniform
measure across different rheumatic diseases has been limited to
comparing just a few rheumatic diseases at a time.3,12
The prevalence of fatigue has been indicated to be more
prevalent in patients with more than one rheumatic disease3 and there
are some indications for a higher prevalence in women2,5 and in people
with a lower social economic status.13 So far, no significant associations
have been reported between fatigue and other demographics such as
age and ethnicity.2 Considering that fatigue is a core symptom of
fibromyalgia,14 a high prevalence of severe fatigue in patients with
fibromyalgia is an obvious expectation. However, while comorbid
fibromyalgia in patients with rheumatoid arthritis has been associated
with severe fatigue,15 there are mixed indications that comorbid
fibromyalgia
is
erythematosus,
associated
16,17
with
fatigue
in
systemic
lupus
and no clear indications of an association in
18,19
Sjögren’s syndrome.
The main objective of the current study was to provide an
overview of the prevalence of severe fatigue across a broad range of
rheumatic diseases in a single large international sample of patients
using a uniform measure of fatigue and a stringent cut-off criterion
indicating a level of fatigue that is comparable with fatigue in patients
with chronic fatigue syndrome. A secondary objective was to examine
whether the prevalence of severe fatigue was associated with having
(comorbid)
fibromyalgia,
having
multiple
rheumatic
diseases
not
including fibromyalgia, and demographic variables.
27
CHAPTER 2
METHODS
Participants
The study population comprised 6120 patients with rheumatic diseases
from different countries who participated in an online study that
examined invalidation. Inclusion criteria were a self-reported diagnosis
of at least one rheumatic disease, being 18 years or older, and speaking
one of the languages in which the online questionnaires were provided
(i.e. Dutch, English, French, German, Portuguese or Spanish). The study
was conducted according to the principles of the Declaration of Helsinki20
and approved by the medical ethical review board of the University
Medical Center Utrecht. Details of the study have been described.21
Materials
Fatigue was measured with the Vitality scale of the RAND(SF)-36 item
Health Survey.22-24 The reliability and validity of this questionnaire have
been tested for all languages included in this study and are satisfactory
in both the general population and in patient samples.25-31 The Vitality
scale assesses fatigue in the last 4 weeks using 4 items scored on a 6point Likert scale. The final score range is 0-100 with lower scores
representing more fatigue. In our study, scores of 35 or lower were
considered to indicate severe fatigue. This cut-off score is similar to the
10th percentile of the general population.32 To identify patients with
chronic fatigue syndrome, this cut-off score was found to have 90%
sensitivity (i.e. 90% of people with chronic fatigue syndrome according
to established classification criteria were correctly identified as having
chronic fatigue syndrome using this cut-off score) and 81% specificity
(i.e. 81% of the people not having chronic fatigue syndrome according
to established classification criteria were correctly identified as not
having chronic fatigue syndrome using this cut-off score).33
Statistical analysis
In descriptive analyses, the cut-off score of ≤ 35 was used to evaluate
the number of patients with severe fatigue for groups of patients with a
single
rheumatic
disease
or
multiple
rheumatic
diseases.
Single
rheumatic diseases were represented by a minimum of 75 patients.
Single rheumatic diseases represented by less than 75 patients were
28
PREVALENCE OF SEVERE FATIGUE
included in analyses as one combined group, “a single other rheumatic
disease”.
Logistic regression analysis examined the following possible
predictors of severe fatigue: having fibromyalgia (yes/no), having
multiple
rheumatic
diseases
without
fibromyalgia
(yes/no),
and
demographic variables gender, age, years of education (≤ 14 and > 14),
marital status (single or divorced/widowed, with being in a relationship
as the reference category), and language (English, French, German,
Portuguese, and Spanish, with Dutch as the reference category).
For the logistic regression analysis, regression coefficients (B),
standard errors (SE), Wald statistics, logistic pseudo partial correlations
(r, i.e. the explanatory value attributable to a single predictor after
adjusting for all other predictors), odds ratios, and goodness of fit of the
whole model (Nagelkerke’s R2) are reported. Significance levels were set
at p < .05. Data were analysed using SPSS 20.
RESULTS
Characteristics of the study population
Table 1 shows the characteristics of the 6120 patients with rheumatic
diseases. Almost half of the patients reported a diagnosis of fibromyalgia
(49%). The most commonly reported combinations of rheumatic
diseases were fibromyalgia and osteoarthritis (n = 511), fibromyalgia
and
osteoarthritis
and
another
rheumatic
disease
(n
=
203),
osteoarthritis and other rheumatic diseases not being fibromyalgia (n =
228 of which 102 had rheumatoid arthritis), and rheumatoid arthritis
and other rheumatic diseases not being osteoarthritis or fibromyalgia (n
= 181). In total, this study covered 30 rheumatic diseases.
Participants resided in various countries around the world. The
most common countries of residence per language were as follows:
Dutch speakers lived mostly in the Netherlands (n = 1613) and Belgium
(n = 236), English speakers in the United Kingdom (n = 450), the
United States of America (n = 104), and Canada (n = 78), German
speakers in Germany (n = 520), French speakers in France (n = 680)
and Belgium (n = 62), Spanish speakers in Spain (n = 811), Argentina
(n = 266), Mexico (n = 132), and Chile (n = 54), and Portuguese
speakers in Portugal (n = 687).
29
CHAPTER 2
Table 1 Characteristics of the 6120 patients with rheumatic diseases
Female sex, n (%)
Age, mean ± SD
Men
Women
Years of education, n (%)
≤ 14 years
> 14 years
Unknown
Marital status, n (%)
Single
Married or in a steady relationship
Divorced or widowed
Unknown
Language, n (%)
Dutch
English
French
German
Portuguese
Spanish
5391
47
50
46
(88)
±12
(12)
(12)
2673
2959
488
(44)
(48)
(8)
962
4475
659
1
(16)
(73)
(11)
(0)
1871
739
787
560
725
1438
(31)
(12)
(13)
(9)
(12)
(23)
a
Rheumatic disease, n (%)
Fibromyalgia
Osteoarthritis
Rheumatoid arthritis
Systemic lupus erythematosus
Ankylosing spondylitis / Bechterew’s disease
Sjögren’s syndrome
Psoriatic arthritis
Scleroderma
Polymyalgia rheumatica
Ehlers-Danlos syndrome or hypermobility syndrome
Juvenile idiopathic arthritis
Gout or pseudogout
Tietze’s syndrome / costochondritis
Mixed connective tissue disease
2993
(49)
1249
(20)
1054
(17)
804
(13)
621
(10)
567
(9)
240
(4)
147
(2)
93
(2)
85
(1)
81
(1)
62
(1)
54
(1)
53
(1)
b
149
(2)
Another Rheumatic disease
a: Due to patients with more than one rheumatic disease, the sum of percentages
mentioned per rheumatic disease exceeds 100%.
b: The most mentioned diseases in the category “another rheumatic disease” are Behçet’s
disease (n = 21), Still’s disease (n = 20), sarcoidosis (n = 18), osteoporosis (n = 16), and
dermatomyositis (n = 11).
30
PREVALENCE OF SEVERE FATIGUE
Prevalence of severe fatigue
The prevalence of severe fatigue is shown in figure 1 for patients with a
single rheumatic disease and patients with multiple rheumatic diseases
with or without fibromyalgia. Severe fatigue was present in 65% of all
patients with percentages from 41% to 57% in patients with a single
inflammatory
rheumatic
disease,
around
80%
in
patients
with
fibromyalgia and 35% in patients with osteoarthritis.
Figure 1. Prevalence of severe fatigue [RAND(SF)-Vitality score ≤ 35] in patients with
rheumatic diseases. Of the 6120 patients, 6034 had a SF-Vitality score; the number of
patients with a missing score ranged per rheumatic disease group from 3 to 16. “A single
other rheumatic disease” included all diagnoses which did not reach the minimum of 75
patients to represent a specific rheumatic population. Patients with multiple rheumatic
diseases were divided into a group with fibromyalgia and a group without fibromyalgia as
one of the diagnoses
31
CHAPTER 2
Table 2 Logistic regression model predicting severe fatigue (RAND(SF)-Vitality ≤ 35)
Fibromyalgia
Multiple rheumatic diseases
without FM
b
c
Gender
Years of education
Marital status
d
1.37 (.07)
387.49***
.23
3.95
0.47 (.11)
20.01***
.05
1.61
2.74
r
Odds ratio
.01
0.86
-0.01 (.003)
22.54***
.05
0.99
-0.31 (.07)
21.94***
.05
0.73
e
Single
Divorced/widowed
Language
Wald statistic
-0.16 (.10)
Age
a
B (SE)
-0.11 (.09)
1.71
.00
0.89
0.02 (.11)
0.04
.00
1.02
f
English
1.11 (.12)
87.94***
.11
3.03
French
1.76 (.12)
201.56***
.17
5.82
German
0.91 (.12)
62.91***
.09
2.49
Portuguese
0.30 (.10)
8.19**
.03
1.35
Spanish
0.71 (.08)
74.84***
.10
2.03
* = p < .05; ** = p < .01; *** = p < .001; “Variance” explained by the total model,
Nagelkerke’s R2 = .23
a: r is the logistic pseudo partial correlation, i.e. the explanatory value attributable to a
single predictor after taking into account all other predictors
b: Having multiple rheumatic diseases without fibromyalgia (FM): yes = 1, no = 0;
c: Gender: male = 1 and female = 0
d: Years of education: > 14 years = 1, ≤ 14 years = 0
e: Marital status : two dummy variables with “in a relationship” as reference category
f: Language: five dummy variables with Dutch as reference category
Associations with severe fatigue
The
logistic
regression
analysis
(Table
2)
showed
that
having
fibromyalgia, having multiple rheumatic diseases without fibromyalgia,
and being a member of the sample that did not speak Dutch increased
patients’ chance of being severely fatigued while being older and having
more years of education decreased patients’ chance. Gender and marital
status did not significantly predict severe fatigue (ps ≥ .10). According
to the partial correlation adjusted for the other variables, having
fibromyalgia was the strongest of all included predictors (r = .23). For
patients with fibromyalgia, it was 4 times more likely to be severely
fatigued than for patients without fibromyalgia. Language was another
strong predictor; most notably, for French speakers, the chance of being
32
PREVALENCE OF SEVERE FATIGUE
severely fatigued was almost 6 times higher than for Dutch speakers.
The logistic analysis showed that, overall, severe fatigue was less likely
in patients who spoke Dutch than in patients with another linguistic
background. Supplementary analyses showed that 64% of Dutch
speaking patients with fibromyalgia were severely fatigued versus 85%
to 91% of patients with fibromyalgia in populations with another
linguistic background. The fit of the total model (Nagelkerke’s R2)
was .23, leaving more than 75% of severe fatigue unexplained.
DISCUSSION
This study in 30 rheumatic diseases shows that severe fatigue is a
widespread and highly prevalent problem across rheumatic diseases.
Overall, one out of every two patients was severely fatigued. Severe
fatigue was least common in patients with osteoarthritis (35%) and
most common in patients with (comorbid) fibromyalgia (around 80%).
Patients’ odds of being severely fatigued were higher when having
fibromyalgia, multiple rheumatic diseases
without
fibromyalgia, a
younger age, and less years of education; also linguistic background
was related to fatigue.
Thorough research into the prevalence of severe fatigue in
rheumatic diseases would demand random sampling, certification of the
rheumatic disease by a medical specialist, and identifying chronic fatigue
according to official classification criteria.34 This type of prevalence
studies have not been done yet. Previous studies examining fatigue
across rheumatic diseases all had their limitations. One study examined
three rheumatic diseases and, like most other studies,5-7,10 used a
sample of patients recruited in one rheumatology clinic.12 Another used
a sample of the general population in which the presence of a rheumatic
disease was determined by self-reported diagnosis and did not present a
cut-off for fatigue or prevalence per rheumatic disease.3 Overall
measures to assess fatigue varied across rheumatic diseases and in
definitions of fatigue severity5-7,9,10 which impeded insight into the
prevalence of severe fatigue in distinct rheumatic diseases. A strength of
our study is that a uniform measure and cut-off were used to estimate
the prevalence in distinct rheumatic diseases. In spite of the diversity of
assessment and sampling methods in all studies thus far, our prevalence
33
CHAPTER 2
estimates are in agreement with previous studies examining the
prevalence of severe fatigue7,12,35 and lower than studies examining
prevalence of less severe levels of fatigue in rheumatic diseases.6,9,36
Although having (comorbid) fibromyalgia increased patients’ odds
of being severely fatigued, this study also clearly showed that severe
fatigue
is
by
no
means
exclusive
to
patients
with
(comorbid)
fibromyalgia; around 50% of patients with other rheumatic diseases are
also severely fatigued. Indeed, fatigue has been recognized in recent
years
as
a
core
symptom
and
outcome
measure
not
only
in
fibromyalgia, but also in rheumatoid arthritis, psoriatic arthritis, and
ankylosing spondylitis.2,5,9,14 Patient focus group discussions indicated
that fatigue is overwhelming and different from normal tiredness, that it
permeates every sphere of life, and that the possibilities of selfmanagement are variable and professional support is rare.2,37 The
current study showed high prevalence of severe fatigue across 30
rheumatic diseases and different cultural backgrounds. This suggests
that fatigue should be considered a core symptom and outcome
measure in clinical trials and treatment for all rheumatic diseases,
without
exception.
Moreover,
the
finding
emphasizes
that
the
development and evaluation of adequate management and treatment of
fatigue in rheumatic diseases is of utmost importance.
The pathology of fatigue is largely unknown. The high prevalence
of fatigue in rheumatic diseases suggests that the inflammatory process
is a precipitating and possible maintaining factor of fatigue. This
interpretation is somewhat supported by the observation of a lower
prevalence of fatigue among patients with osteoarthritis, but it is
contradicted by the high prevalence being observed in fibromyalgia.
Moreover, associations of clinical and laboratory variables with fatigue
are mostly low or absent.1,2 With current knowledge, “acute” fatigue as
a
result
of
a
disease
flare-up
is
probably
best
targeted
by
pharmacological interventions, while behavioural means such as lifestyle adjustment, cognitive behavioural therapy, (graded) physical
exercise training, and sleep hygiene interventions should be considered
in the treatment of chronic fatigue.1,38,39
The presence of severe fatigue varied substantially across
languages with French speaking patients most often reporting severe
34
PREVALENCE OF SEVERE FATIGUE
fatigue and Dutch speaking patients least often. Similar findings have
been reported for functioning and well-being, as measured with the
RAND(SF)-36, both between countries and between language regions,
with Dutch speakers having more favourable scores than people with
another language and French speakers scoring relatively poor.40,41 These
differences do not seem to be due to measurement invariance40,42 but
have been attributed to differences in access to and quality of national
health systems43 and differences in social and economic opportunities
within countries.44,45
The current study has some limitations. It was based on selfreported diagnoses of rheumatic diseases without certification by a
medical specialist. Moreover, the recruitment through the internet might
have led to a lower representation of the older patient population and
patients with a low social economic class, and it surely led to an
overrepresentation of some patient groups. A strength of the study is
that a stringent uniform cut-off score was used. However, although this
cut-off has been shown sensitive to identify patients with chronic fatigue
syndrome in the general population,33 it is recommended to examine in
future studies whether this cut-off score is equally sensitive to identify
chronic fatigue syndrome according classification criteria34 in patients
with rheumatic diseases.
This study is the first to provide an overview of the presence of
severe fatigue across 30 rheumatic diseases using a large international
dataset, a uniform way of recruitment, a uniform measure to assess
fatigue, and a verified32,33 cut-off score for severe fatigue. It showed
that more than 50% of all patients with a rheumatic disease are
severely fatigued. Severe fatigue can have detrimental effects for the
patient,
the
near
environment,
and
society
at
large.
A
better
understanding of fatigue is crucial. In rheumatology, unravelling the
underlying mechanisms of fatigue and developing optimal treatments
should be top priorities in research and clinical practice.
ACKNOWLEDGEMENTS
The authors thank all participants for their contribution to this study and
the patient associations for help in recruiting participants.
35
CHAPTER 2
REFERENCES
1.
Stebbings S, Treharne GJ. Fatigue in rheumatic disease: an overview. Int J Clin
Rheumatol 2010;5:487–502.
2.
Hewlett S, Nicklin J, Treharne GJ. Fatigue in musculoskeletal conditions. Arthritis Res
UK Top Rev 2008;6:1.
3.
Picavet HS, Hoeymans N. Health related quality of life in multiple musculoskeletal
diseases: SF-36 and EQ-5D in the DMC3 study. Ann Rheum Dis 2004;63:723-9.
4.
Repping-Wuts H, van Riel P, van Achterberg T. Rheumatologists' knowledge, attitude
and current management of fatigue in patients with rheumatoid arthritis(RA). Clin
Rheumatol 2008;27:1549-55.
5.
Husted JA, Tom BD, Schentag CT, Farewell VT, Gladman DD. Occurrence and
correlates of fatigue in psoriatic arthritis. Ann Rheum Dis 2009;68:1553-8.
6.
Tench CM, McCurdie I, White PD, D'Cruz DP. The prevalence and associations of
fatigue in systemic lupus erythematosus. Rheumatology 2000;39:1249-54.
7.
Barendregt PJ, Visser MR, Smets EM, et al. Fatigue in primary Sjögren's syndrome.
Ann Rheum Dis 1998;57:291-5.
8.
Power JD, Badley EM, French MR, Wall AJ, Hawker GA. Fatigue in osteoarthritis: a
qualitative study. BMC Musculoskelet Disord 2008;9:63.
9.
Van Tubergen A, Coenen J, Landewé R, et al. Assessment of fatigue in patients with
ankylosing spondylitis: a psychometric analysis. Arthritis Rheum 2002;47:8-16.
10.
Sandusky SB, McGuire L, Smith MT, Wigley FM, Haythornthwaite JA. Fatigue: an
overlooked
determinant
of
physical
function
in
scleroderma.
Rheumatology
2009;48:165-9.
11.
Dupond
JL. Fatigue
in patients
with rheumatic
diseases. Joint Bone Spine
2011;78:156-60.
12.
Wolfe F, Hawley DJ, Wilson K. The prevalence and meaning of fatigue in rheumatic
disease. J Rheumatol 1996;23:1407-17.
13.
Khlat M, Chau N, Guillemin F, et al. Social disparities in musculoskeletal disorders
and associated mental malaise: findings from a population-based survey in France.
Scand J Public Health 2010;38:495-501.
14.
Wolfe F, Clauw DJ, Fitzcharles MA, et al. The American College of Rheumatology
preliminary diagnostic criteria for fibromyalgia and measurement of symptom
severity. Arthritis Care Res 2010;62:600-10.
15.
Wolfe F, Michaud K. Severe rheumatoid arthritis (RA), worse outcomes, comorbid
illness,
and
sociodemographic
disadvantage
characterize
RA
patients
with
fibromyalgia. J Rheumatol 2004;31:695-700.
16.
Taylor J, Skan J, Erb N, et al. Lupus patients with fatigue-is there a link with
fibromyalgia syndrome? Rheumatology 2000;39:620-3.
17.
Bruce IN, Mak VC, Hallett DC, Gladman DD, Urowitz MB. Factors associated with
fatigue in patients with systemic lupus erythematosus. Ann Rheum Dis 1999;58:37981.
18.
Hartkamp A, Geenen R, Kruize AA, et al. Serum dehydroepiandrosterone sulphate
levels and laboratory and clinical parameters indicating expression of disease are not
36
PREVALENCE OF SEVERE FATIGUE
associated with fatigue, well-being and functioning in patients with primary Sjogren’s
syndrome. Clin Exp Rheumatol 2011;29:318-21.
19.
Giles I, Isenberg D. Fatigue in primary Sjögren’s syndrome: Is there a link with the
fibromyalgia syndrome? Ann Rheum Dis 2000;59:875-8.
20.
World Medical Association (WMA). Declaration of Helsinki. Seoul: WMA, October
2008.
http://www.wma.net/en/20activities/10ethics/10helsinki/index.html
(last
accessed 2013 November 8).
21.
Kool MB, van de Schoot R, López-Chicheri García I, et al. Measurement invariance of
the Illness Invalidation Inventory (3*I) across language, rheumatic disease and
gender. Ann Rheum Dis 2014;73:551-6.
22.
Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I.
Conceptual framework and item selection. Med Care 1992;30:473-83.
23.
Hays RD, Sherbourne CD, Mazel RM. The RAND 36-item health survey 1.0. Health
Econ 1993;2:217-27.
24.
Van der Zee KI, Sanderman R. Het meten van de algemene gezondheidstoestand
met de RAND-36, een handleiding [Measuring general health status with the RAND36, user Manual]. Groningen: Northern Center of Health Care Research 1994.
25.
Van der Zee KI, Sanderman R, Heyink JW, de Haes H. Psychometric qualities of the
RAND 36-item Health Survey 1.0: a multidimensional measure of general health
status. Int J Behav Med 1996;3:104-22.
26.
Ware JE Jr, Gandek B. Overview of the SF-36 Health Survey and the International
Quality of Life Assessment (IQOLA) Project. J Clin Epidemiol 1998;51:903-12.
27.
Moorer P, Suurmeije ThP, Foets M, Molenaar IW. Psychometric properties of the
RAND-36 among three chronic diseases (multiple sclerosis, rheumatic diseases and
COPD) in The Netherlands. Qual Life Res 2001;10:637-45.
28.
Bulliger M. German translation and psychometric testing of the SF-36 Health Survey:
preliminary results from the IQOLA project. Soc Sci Med 1995;41:1359-66.
29.
Alonso J, Prieto L, Ferrer M, et al. Testing the measurement properties of the Spanish
version of the SF-36 Health Survey among male patients with chronic obstructive
pulmonary disease. J Clin Epidemiol 1998;51:1087-94.
30.
Lopes Ferreira P. Creation of the Portuguese version of MOS SF-36 part II –
validation tests. Acta Med Port 2000;13:119-27.
31.
Perneger TV, Leplège A, Etter JF, Rougemont A. Validation of a French-language
version of the MOS 36-item Short Form Health Survey (SF-36) in young healthy
adults. J Clin Epidemiol 1995;48:1051-60.
32.
Dagfinrud H, Vollestad NK, Loge JH, Kvien TK, Mengshoel AM. Fatigue in patients with
ankylosing spondylitis: A comparison with the general population and associations
with clinical and self-reported measures. Arthritis Rheum 2005;53:5-11.
33.
Jason L, Brown M, Evans M, et al. Measuring substantial reductions in functioning in
patients with chronic fatigue syndrome. Disabil Rehabil 2011;33:589-98.
34.
Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. The chronic
fatigue
syndrome:
International
a
Chronic
comprehensive
Fatigue
approach
Syndrome
to
Study
its
definition
Group.
Ann
and
Intern
study.
Med
1994;121:953-9.
37
CHAPTER 2
35.
Van Hoogmoed D, Fransen J, Bleijenberg G, van Riel P. Physical and psychosocial
correlates of severe fatigue in rheumatoid arthritis. Rheumatology 2010;49:1294–
1302.
36.
Segal B, Thomas W, Rogers T, et al. Prevalence, severity, and predictors of fatigue in
subjects with primary Sjögren's syndrome. Arthritis Rheum. 2008;59:1780-7.
37.
Kirwan J, Minnock P, Adebajo A, et al. Patient perspective: fatigue as a recommended
patient
centered
outcome
measure
in
rheumatoid
arthritis.
J
Rheumatol
2007;34:1174-7.
38.
Davies H, Brophy S, Dennis M, Cooksey R, Irvine E, Siebert S. Patient perspectives of
managing fatigue in Ankylosing Spondylitis, and views on potential interventions: a
qualitative study. BMC Musculoskelet Disord 2013;14:163.
39.
Prins JB, Van der Meer JWM, Bleijenberg G. Chronic fatigue syndrome. Lancet
2006;367:346-55.
40.
Razavi D, Gandek B. Testing Dutch and French translations of the SF-36 Health
Survey among Belgian angina patients. J Clin Epidemiol 1998;51:975-81.
41.
Sprigg N, Gray LJ, Bath PM, et al. Quality of life after ischemic stroke varies in
western countries: data from the tinzaparin in Acute Ischaemic StrokeTrial (TAIST). J
Stroke Cerebrovasc Dis 2012;21:587-93.
42.
Wagner AK, Gandek B, Aaronson NK, et al. Cross-cultural comparisons of the content
of SF-36 translations across 10 countries: results from the IQOLA Project.
International Quality of Life Assessment. J Clin Epidemiol 1998;51:925-32.
43.
Macinko J, Starfield B, Shi L. The contribution of primary care systems to health
outcomes within Organization for Economic Cooperation and Development (OECD)
countries, 1970-1998. Health Serv Res 2003;38:831-65.
44.
Pagán-Rodríguez R, Pérez S. Depression and self-reported disability among older
people in Western Europe. J Aging Health 2012;24:1131-56.
45.
Assi J, Lucchini M, Spagnolo A. Mapping patterns of well-being and quality of life in
extended Europe. Int Rev Econ 2012;59:409-30.
38
Chapter 3
Fatigue in patients with
quiescent systemic lupus
erythematosus: The role of
dehydroepiandrosterone
sulphate
Cécile L. Overman
André Hartkamp
Ercolie R. Bossema
Marc Bijl
Guido L.R. Godaert
Johannes W.J. Bijlsma
Ronald H.W.M. Derksen
Rinie Geenen
Published as:
Overman, C.L., Hartkamp, A., Bossema, E.R., Bijl, M., Godaert, G.L.R.,
Bijlsma, J.W.J., Derksen, R.H.W.M. & Geenen, R. (2012). Fatigue in
patients with systemic lupus erythematosus: The role of
dehydroepiandrosterone sulphate. Lupus, 21, 1515-1521.
39
CHAPTER 3
ABSTRACT
Background:
Fatigue
is
a
major
problem
in
systemic
lupus
erythematosus (SLE), but the physiological substrate of this fatigue is
largely unclear.
Objective: To examine if low levels of dehydroepiandrosterone (DHEA)
and its sulphate DHEAS play a role in SLE fatigue.
Methods: We compared 1) DHEAS levels and fatigue between 60
female patients with quiescent SLE (31 using, 29 not using prednisone)
and 60 age-matched healthy women, and 2) fatigue between SLE
patients with low and normal DHEAS levels. Serum DHEAS levels were
determined
with
an
Advantage
Chemiluminescense
System.
The
Multidimensional Fatigue Inventory (MFI) was used to assess fatigue.
Results: Patients were more fatigued (p ≤ .001) than healthy women
and more often had below-normal DHEAS levels (p < .001). Patients
using prednisone with low and normal DHEAS levels reported a similar
level of fatigue (p ≥ .39). Patients with low DHEAS levels not using
prednisone reported less fatigue than those with normal DHEAS levels (p
≤ .03).
Conclusion: Our results indicate that low DHEAS levels in SLE are not –
or even inversely – related to fatigue. After our previous finding that
DHEA administration does not reduce fatigue, this result further
indicates that low DHEA(S) levels alone do not offer an explanation for
SLE fatigue.
40
FATIGUE IN PATIENTS WITH SLE: THE ROLE OF DHEAS
INTRODUCTION
Systemic lupus erythematosus (SLE) is a systemic autoimmune disease
with clinical presentations such as inflammation of joints, skin, visceral
membranes and kidneys.1,2 Fatigue is a prominent, often debilitating
feature of the disease.3-9 Up to 80% of patients experience fatigue, even
when the disease is in remission.4,8,9 To date, the physiological origin of
fatigue in SLE is largely unclear. Some studies suggested a correlation
between fatigue and SLE disease activity, cytokine or autoantibody
levels,8,10 while other studies were inconclusive,11 or argued against any
relation.5,6,9,12
Attention
inflammatory
has
and
been
directed
vitalizing
towards
influence
the
of
possible
the
anti-
hormone
dehydroepiandrosterone (DHEA) and its sulphate ester (DHEAS) in
SLE.13 DHEA and DHEAS are the most abundantly produced androgens
in humans, secreted by the adrenal glands in response to activity of the
hypothalamic-pituitary-adrenal axis (HPA-axis). Compared to healthy
subjects, mean levels of DHEA(S) are low in patients with SLE.13-15
Studies in aging people and some patient populations suggested that
lower levels of circulating DHEA(S) are related to more fatigue. 13 In
patients with adrenal insufficiency, DHEA substitution therapy reduced
fatigue.16,17 In SLE, most studies examining DHEA supplementation did
not specifically assess fatigue as an outcome measure, but improvement
in health, global wellbeing and functioning was observed. 18-21
The low mean DHEA(S) levels in SLE, together with fatigue being
a major problem in most SLE patients, was the basis for our attempt to
examine the association between endogenous levels of DHEA(S) and
fatigue in SLE. We used baseline data of our previous intervention trial 22
to compare serum DHEAS levels and multiple dimensions of fatigue
between female patients with SLE and age-matched healthy women,
and to compare fatigue between patients with SLE with low and normal
DHEAS levels. Since disease activity may influence both DHEAS levels
and fatigue,8,10 only patients with SLE with a low level of disease activity
were included in the study. Moreover, because prednisone may reduce
serum DHEA(S) levels13 and improve perceived health,23 this study,
unlike previous studies, differentiated between patients using and not
using prednisone. Patients with SLE were expected to have lower levels
41
CHAPTER 3
of serum DHEAS and higher fatigue levels than healthy controls.
Furthermore, patients with SLE with low DHEAS levels were expected to
report more fatigue than those with normal DHEAS levels.
METHODS
Participants
Included were 60 female patients with SLE with a low level of disease
activity who were willing to participate in a placebo-controlled study on
effects of administration of DHEA on wellbeing and fatigue22 and 60 agematched healthy women. Patients were recruited from the departments
of Rheumatology and Clinical Immunology of the University Medical
Centers of Utrecht and Groningen. They fulfilled at least four American
College of Rheumatology (ACR) SLE classification criteria 24 and were
aged  18 years. All of the patients were in clinical remission according
to assessment by an experienced rheumatologist. Exclusion criteria were
pregnancy, wish to conceive, malignancy within the preceding 5 years,
daily use of glucocorticosteroids > 10 mg in the preceding 6 months and
abnormal thyroid stimulating hormone or creatinine levels, or abnormal
liver function. Age- and sex-matched control subjects were recruited by
patients among friends, family members and acquaintances. They did
not take medications and were not known with a disease. The research
and ethics committee of both institutions approved of the study. All
participants provided written informed consent.
Assessments
The assessments of the patients with SLE involved the baseline data of
our placebo-controlled trial on effects of DHEA administration.22 Serum
levels of DHEAS were measured using an Advantage Chemiluminescense
System (Nichols Institute Diagnostics, San Juan Capistrano, USA) 25 with
a lower detection limit of 0.2 µmol/L and an inter-assay variation of <
11%. Normal values in our laboratory are 1-9 µmol/L, 1-7 µmol/L, and
0.5-5 µmol/L for women aged 20-40, 40-50, and > 50 years,
respectively. Clinical assessments included serum anti-double-stranded
DNA (anti-dsDNA) antibodies, serum C3 and C4, SLE disease activity
index (SLEDAI)26 and erythrocyte sedimentation rate (ESR). Fatigue was
measured
42
with
five
dimensions
of
the
Multidimensional
Fatigue
FATIGUE IN PATIENTS WITH SLE: THE ROLE OF DHEAS
Inventory (MFI): general fatigue, physical fatigue, reduced activity,
reduced motivation and mental fatigue. The score range per dimension
is 4-20, with higher scores indicating more fatigue.27
Statistical analysis
Chi2-tests, independent samples t-tests and Mann-Whitney U tests were
used
to
examine
differences
between
patients
with
SLE
using
prednisone, patients with SLE not using prednisone and healthy controls
with respect to frequencies (Caucasian y/n, education level, marital
status, pre- or postmenopausal status, low/normal DHEAS level,
medication use), continuous variables with a normal score distribution
(age, disease duration, C3), and continuous variables with a non-normal
score distribution (SLEDAI, anti-dsDNA, C4, ESR, DHEAS, MFI fatigue
scores). The possible influence of differences in menopausal status
between patients and controls was checked. Within the two SLE groups,
Mann-Whitney U tests were used to examine differences in fatigue
between patients with low and normal DHEAS levels. Common threshold
values were used to differentiate between these low and normal DHEAS
levels. Statistical analyses were performed with SPSS Version 16.0. All
tests were two-sided and p < .05 was considered significant.
RESULTS
Participant characteristics
Figure 1 gives an impression of the study population by indicating the
ACR criteria for the classification of SLE24 that were fulfilled at the time
of study. Apart from serological findings, arthritis and haematological
abnormalities were the most frequent clinical manifestations. About one
third had a history of lupus nephritis. In all patients, SLE was in stable
clinical remission. This is also reflected in the low SLEDAI scores,26,28,29
with only serological and haematological findings being the cause of
scores above zero. Overall, 85% of patients had a SLEDAI score of ≤ 4
and the maximum score was 6. These scores are in the range of
previous established SLEDAI cut-off scores for inactive disease.28,29
Thirty-one patients with SLE used a low dose of prednisone
(median dose 5 mg, range 2.5-10.0 mg). As shown in Table 1, patients
with SLE using prednisone, patients with SLE not using prednisone and
43
CHAPTER 3
healthy control subjects did not significantly differ from each other on
demographic variables (p ≥ .11). Patients with SLE using prednisone did
have lower C4 levels (p = .047) and more often used azathioprine (p =
.004) than those not using prednisone, but the two patient groups did
not significantly differ on other disease activity variables (SLEDAI, p =
.18; anti-dsDNA, p = .33; C3, p = .052; ESR, p = .50) or other
medication use (paracetamol, non-steroidal anti-inflammatory drugs,
hydroxychloroquine, methotrexate, β-blockers and antidepressants; p ≥
.16; data not shown).
Figure 1. ACR criteria for the classification of SLE fulfilled by our patients.
Fatigue and DHEAS levels in the SLE group versus the control
group
The bottom of Table 1 shows the median scores for the five fatigue
dimensions, median DHEAS levels and the number of participants with
serum DHEAS levels below or above the lower limit of normal. Patients
with SLE using and not using prednisone did not differ from each other
on any of the five fatigue dimensions (p ≥ .49), but compared to healthy
control subjects, patients with SLE reported more fatigue on all
dimensions (p ≤ .001). DHEAS levels differed significantly between the
three groups (Figure 2). DHEAS levels of patients with SLE using
prednisone were lower than those of patients with SLE not using
44
FATIGUE IN PATIENTS WITH SLE: THE ROLE OF DHEAS
prednisone (U = 184.0, p < .001) and DHEAS levels of the total SLE
group (Median = 0.79) were lower than of the control group (U = 620.0,
p < .001). In the SLE group, 77% of the patients using prednisone and
24% of the patients not using prednisone had a below-normal serum
DHEAS level.
The control group included less postmenopausal women than the
SLE group, but repeating the analyses for only premenopausal women
did not change results: premenopausal patients with SLE were more
fatigued on all dimensions (174.0 ≤ U ≤ 578.0, p ≤ .002) and had lower
DHEAS levels (U = 355.0, p < .001) than premenopausal controls.
Fatigue in SLE subgroups with low versus normal DHEAS levels
Within the entire SLE group, patients with low and patients with normal
DHEAS levels did not differ on any of the five fatigue dimensions (U ≥
349.5, p ≥ .14; data not shown). Table 2 shows the median fatigue
scores of the patients with SLE related to DHEAS level and use of
prednisone. In patients with SLE using prednisone, fatigue did not differ
between patients with low and normal DHEAS levels. In the SLE group
not using prednisone, those with low DHEAS levels reported less fatigue
than those with normal DHEAS levels on four of the five fatigue
dimensions (U ≤ 33.5, p ≤ .03); this is illustrated in Figure 3 for the
general fatigue dimension. These findings were not due to differences in
inflammation; ESR did not differ between patients with low DHEAS levels
and patients with normal DHEAS levels (U = 61.5, p = .43 in the SLE
group not using prednisone and U = 62.0, p = .30 in the SLE group
using prednisone).
45
CHAPTER 3
Table 1. Characteristics of SLE patients using and not using prednisone and healthy
controls.
SLE
SLE
using
not using
prednisone
prednisone
(n = 31)
(n = 29)
41.8 ± 10.6
43.8 ± 10.9
(21-64)
(28-71)
12.8 ± 7.4
12.3 ± 6.9
(2-32)
(2-28)
27 (87)
25 (86)
p1
Healthy
p2
controls
(n = 60)
Demographic variables
Age, years,
mean ± SD (range)
Disease duration in years,
mean ± SD (range)
Caucasian, n (%)
Education level, n (%)
a
.48
43.2 ± 10.7
.80
n/a
.92
57 (95)
.97
12 (39)
12 (41)
21 (35)
Middle
13 (42)
12 (41)
24 (40)
6 (19)
5 (17)
High
Married
Widowed/divorced
Postmenopausal, n (%)
15 (25)
.75
Single
b
.36
.66
Low
Marital status, n (%)
.85
(21-70)
.13
4 (13)
6 (21)
5 (8)
22 (71)
18 (62)
51 (85)
5 (16)
5 (17)
10 (32)
8 (28)
.69
15.0
14.0
.49
(13.0-18.0)
(11.5-17.5)
4 (7)
9 (15)
.11
5.0
<.001
Fatigue, median
(interquartile range)
MFI general fatigue
MFI physical fatigue
MFI reduced activity
MFI reduced motivation
MFI mental fatigue
DHEAS, nmol/L, median
(interquartile range)
14.0
12.0
(11.0-16.0)
(8.5-16.0)
10.0
12.0
(8.0-13.0)
(8.5-13.5)
10.0
9.0
(7.0-12.0)
(6.0-12.0)
8.0
11.0
(6.0-13.0)
(6.0-12.5)
0.46
1.90
(0.10-0.82)
(0.73-3.15)
DHEAS level, n (%)
low
normal
(4.0-8.0)
.63
5.0
<.001
(4.0-7.8)
.76
5.0
<.001
(4.0-7.8)
.57
4.0
<.001
(4.0-6.0)
.81
5.5
<.001
(4.0-8.8)
<.001
2.95
<.001
(2.00-4.18)
<.001
<.001
24 (77)
7 (24)
1 (2)
7 (23)
22 (76)
59 (98)
DHEAS: Dehydroepiandrosterone sulphate; MFI: Multidimensional Fatigue Inventory with
higher scores reflecting more fatigue (range 4-20); p1: significance of the difference
between the two SLE groups; p2: significance of the difference between the total SLE
group and the control group; SLE: systemic lupus erythematosus;
46
FATIGUE IN PATIENTS WITH SLE: THE ROLE OF DHEAS
a: Education level was defined as low (primary school or lower vocational secondary
education), middle (intermediate general secondary education or intermediate vocational
education), and high (higher general secondary education, higher vocational education, or
university education);
b: Postmenopausal status was defined by amenorrhea for at least one year in women with
a uterus in situ and in hysterectomised women by serum follicle-stimulating hormone level
> 35 IU/litre.
Figure 2. DHEAS levels in patients with SLE using and not using prednisone and healthy
controls. Data are shown as dots for every participant and as boxplots. Each box
represents the 25th to 75th percentile. Bars outside the boxes represent the 10th to 90th
percentile.
DHEAS:
Dehydroepiandrosterone
sulphate;
SLE:
systemic
lupus
erythematosus. The median patient score on the SLE Disease Activity Index was 4
(interquartile range 2-4, maximum 6).
47
CHAPTER 3
Table 2. Median MFI fatigue scores (interquartile ranges) in SLE subgroups with low
versus normal DHEAS levels.
SLE using prednisone
MFI
General
fatigue
Low
Normal
DHEAS
DHEAS
(n = 24)
(n = 7)
15.5
13.0
U
SLE not using prednisone
p
66.0
.39
67.0
.42
74.0
.64
69.0
.48
84.0
1.00
(13.0-18.8) (12.0-17.0)
Physical
14.0
12.0
fatigue
(11.0-16.5)
(8.0-16.0)
10.5
10.0
(8.0-13.0)
(5.0-19.0)
10.0
10.0
Reduced
activity
Reduced
motivation
(7.0-12.8)
(6.0-12.0)
Mental
8.5
8.0
fatigue
(5.5-13.0)
(6.0-12.0)
Low
Normal
DHEAS
DHEAS
(n = 7)
(n = 22)
10.0
15.0
(8.0-12.0)
(13.0-19.3)
9.0
13.5
(7.0-12.0)
(9.8-17.0)
5.0
12.0
(5.0-12.0)
(10.8-14.3)
6.0
11.0
(4.0-8.0)
(7.8-12.0)
8.0
11.0
(4.0-12.0)
(6.8-13.0)
U
p
22.0 .005
33.5
.03
26.0 .009
24.5 .007
60.0
.38
DHEAS: Dehydroepiandrosterone sulphate; MFI: Multidimensional Fatigue Inventory with
higher scores reflecting more fatigue (range 4-20); SLE: systemic lupus erythematosus;
U: Mann-Whitney U.
DISCUSSION
To elucidate the possible role of endogenous DHEAS levels in SLE
fatigue, serum DHEAS levels and fatigue were examined in female
patients with SLE with a low level of disease activity and in female
healthy control subjects. As expected, more patients with SLE had low
DHEAS levels and they also reported more fatigue than healthy controls.
Contrary to our expectations, patients with SLE with low DHEAS levels
reported similar or even less fatigue than patients with SLE with normal
DHEAS levels.
In SLE,13-15 but also in other chronic autoimmune diseases with
high levels of fatigue, such as rheumatoid arthritis 30 and Sjögren’s
syndrome,25 DHEAS levels are found to be low. In contrast, in noninflammatory disorders characterized by fatigue, such as chronic fatigue
syndrome (CFS), depression and burnout, both low 31-33 and high34-38
DHEA(S) levels have been found. Therefore, it could be that low levels
of DHEAS are rather a marker of chronic inflammation than of fatigue.
Nevertheless, the low DHEAS and high fatigue levels in patients with SLE
suggest an association between the two.
48
FATIGUE IN PATIENTS WITH SLE: THE ROLE OF DHEAS
Figure 3. MFI general fatigue scores in patients with SLE not using prednisone with low
versus normal DHEAS levels. Data are shown as dots for every patient and as boxplots.
Each box represents the 25th to 75th percentile. Bars outside the boxes represent the 10 th
to 90th percentile. DHEAS: Dehydroepiandrosterone sulphate; MFI: Multidimensional
Fatigue Inventory with higher scores reflecting more fatigue (range 4-20); SLE: systemic
lupus erythematosus. Of patients not using prednisone, the median score on the SLE
Disease Activity Index was 2 (interquartile range 0-4, maximum 6).
In the total SLE group, fatigue and DHEAS levels were unrelated
and in the absence of prednisone, fatigue was even less in patients with
low DHEAS levels than in patients with normal DHEAS levels. A possible
explanation for this unexpected result may be that fatigue is not
influenced by low DHEA(S) levels as such, but rather by an overall
physiological imbalance involving DHEA(S) and other hormones, such as
cortisol. Previous studies in SLE suggest a hypo-responsive HPA-axis
related to inflammation.39-41 In non-inflammatory disorders involving
49
CHAPTER 3
fatigue,
a
observed,
higher
35,38
and cortisol.
than
normal
DHEA(S):cortisol
ratio
has
been
as well as simultaneously elevated levels of both DHEA(S)
34,36
Our current results do not rule out the existence of a
DHEA(S)/cortisol imbalance reflecting impaired HPA-axis functioning due
to inflammation, or fatigue in SLE. This is a topic for future inquiry.
Research on the relation between endogenous DHEA(S) levels
and fatigue in SLE is scarce. As reviewed,1 most studies examined the
effects of administering
DHEA
in
patients with
SLE, who often
simultaneously used glucocorticoids and had clinically relevant disease
activity. Our study is the first that specifically focused on the possible
role of endogenous DHEAS levels in fatigue of patients with SLE with low
disease activity. Our study has various strengths. Patients and controls
were matched on sex and age, prednisone use was taken into account
and the possible effect of disease activity was minimized by only
including patients with a low level of disease activity. However, our
study also has some limitations. Perhaps DHEAS levels in the brain are
more relevant to fatigue than serum levels; serum DHEAS levels may
not optimally reflect neural DHEAS. 42 In addition, although DHEAS and
DHEA levels are related, our findings do not necessarily fully generalize
to DHEA.13,43 For future research it is recommended that, besides
disease activity and use of immunosuppressive drugs, also other aspects
of HPA-axis functioning, such as cortisol and DHEA, are taken into
account to examine the possible imbalance of adrenal products which
may be associated with SLE fatigue.
The results of the current study indicate that fatigue in patients
with SLE is unrelated to low endogenous DHEAS levels. In the group of
patients not using prednisone, levels of fatigue were even higher with
higher DHEAS levels. Together with the results of our randomized
controlled trial showing no effect of DHEA administration on fatigue over
the placebo effect,22 this suggests that neither DHEA nor its sulphate are
instrumental alone in determining the level of fatigue in SLE.
50
FATIGUE IN PATIENTS WITH SLE: THE ROLE OF DHEAS
REFERENCES
1.
Crosbie D, Black C, McIntyre L, Royle PL, Thomas S. Dehydroepiandrosterone for
systemic lupus erythematosus. Cochrane Database Syst Rev 2007;CD005114.
2.
D'Cruz DP, Khamashta MA, Hughes GRV. Systemic lupus erythematosus. Lancet
2007;369:587-96.
3.
Cleanthous S, Tyagi M, Isenberg DA, Newman SP. What do we know about selfreported fatigue in systemic lupus erythematosus? Lupus. Epub ahead of print 16
February 2012. DOI: 10.1177/0961203312436863
4.
Bruce IN, Mak VC, Hallett DC, Gladman DD, Urowitz MB. Factors associated with
fatigue in patients with systemic lupus erythematosus. Ann Rheum Dis 1999;58:37981.
5.
Burgos PI, Alarcón GS, McGwin Jr. G, Crews KQ, Reveille JD, Vilá LM. Disease activity
and damage are not associated with increased levels of fatigue in systemic lupus
erythematosus
patients
from
a
multiethnic
cohort:
LXVII.
Arthritis
Rheum
2009;61:1179-86.
6.
Omdal R, Mellgren SI, Koldingsnes W, Jacobsen EA, Husby G. Fatigue in patients with
systemic
lupus
antiphospholipid
erythematosus:
Lack
of
antibodies,
other
disease
or
associations
to
serum
characteristics.
J
cytokines,
Rheumatol
2002;29:482-6.
7.
Sweet JJ, Doninger NA, Zee PC, Wagner LI. Factors influencing cognitive function,
sleep, and quality of life in individuals with systemic lupus erythematosus: A review
of the literature. Clin Neuropsychol 2004;18:132-47.
8.
Tench CM, McCurdie I, White PD, D'Cruz DP. The prevalence and associations of
fatigue in systemic lupus erythematosus. Rheumatology (Oxford) 2000; 39:1249-54.
9.
Wang B, Gladman DD, Urowitz MB. Fatigue in lupus is not correlated with disease
activity. J Rheumatol 1998;25:892-5.
10.
Tayer WG, Nicassio PM, Weisman MH, Schuman C, Daly J. Disease status predicts
fatigue in systemic lupus erythematosus. J Rheumatol 2001;28:1999-2007.
11.
Da Costa D, Dritsa M, Bernatsky S, et al. Dimensions of fatigue in systemic lupus
erythematosus: Relationship to disease status and behavioral and psychosocial
factors. J Rheumatol 2006;33:1282-8.
12.
Jump RL, Robinson ME, Armstrong AE, Barnes EV, Kilbourn KM, Richards HB. Fatigue
in systemic lupus erythematosus: Contributions of disease activity, pain, depression,
and perceived social support. J Rheumatol 2005;32:1699-705.
13.
Derksen RHWM. Dehydroepiandrosterone (DHEA) and systemic lupus erythematosus.
Semin Arthritis Rheum 1998;27:335-47.
14.
Hedman M, Nilsson E, De la Torre B. Low sulpho-conjugated steroid hormone levels
in systemic lupus erythematosus (SLE). Clin Exp Rheumatol 1989;7:583-8.
15.
Lahita RG, Bradlow HL, Ginzler E. Low plasma androgens in women with systemic
lupus erythematosus. Arthritis Rheum 1987;30:241-8.
16.
Arlt W. Dehydroepiandrosterone replacement therapy. Curr Opin Endocrinol Diabetes
2006;13:291-305.
51
CHAPTER 3
17.
Hunt PJ, Gurnell EM, Huppert FA, et al. Improvement in mood and fatigue after
dehydroepiandrosterone replacement in Addison's disease in a randomized, double
blind trial. J Clin Endocrinol Metab 2000;85:4650-6.
18.
Chang D-, Lanv J-, Lin H-, Luo S-. Dehydroepiandrosterone treatment of women with
mild-to-moderate systemic lupus erythematosus: A multicenter randomized, doubleblind, placebo-controlled trial. Arthritis Rheum 2002;46:2924-7.
19.
Nordmark G, Bengtsson C, Larsson A, Karlsson FA, Sturfelt G, Rönnblom L. Effects of
dehydroepiandrosterone supplement on health-related quality of life in glucocorticoid
treated
female
patients
with
systemic
lupus
erythematosus.
Autoimmunity
2005;38:531-40.
20.
Van Vollenhoven RF, Engleman EG, McGuire JL. Dehydroepiandrosterone in systemic
lupus erythematosus: Results of a double-blind, placebo-controlled, randomized
clinical trial. Arthritis Rheum 1995;38:1826-31.
21.
Petri MA, Mease PJ, Merrill JT, et al. Effects of prasterone on disease activity and
symptoms in women with active systemic lupus erythematosus: Results of a
multicenter randomized, double-blind, placebo-controlled trial. Arthritis Rheum
2004;50:2858-68.
22.
Hartkamp A, Geenen R, Godaert GLR, Bijl M, Bijlsma JWJ, Derksen RHWM. Effects of
dehydroepiandrosterone on fatigue and well-being in women with quiescent systemic
lupus erythematosus: A randomised controlled trial. Ann Rheum Dis 2010;69:11447.
23.
Thumboo J, Fong KY, Chan SP, Leong KH, Feng PH, Thio ST, et al. A prospective
study of factors affecting quality of life in systemic lupus erythematosus. J Rheumatol
2000;27:1414-20.
24.
Tan EM, Cohen AS, Fries JF. The 1982 revised criteria for the classification of
systemic lupus erythrematosus. Arthritis Rheum 1982;25:1271-7.
25.
Hartkamp A, Geenen R, Godaert GLR, et al. Effect of dehydroepiandrosterone
administration on fatigue, well-being, and functioning in women with primary Sjögren
syndrome: A randomised controlled trial. Ann Rheum Dis 2008;67:91-7.
26.
Bombardier C, Gladman DD, Urowitz MB, Caron D, Chi Hsing Chang. Derivation of the
SLEDAI: A disease activity index for lupus patients. Arthritis Rheum 1992;35:630-40.
27.
Smets EMA, Garssen B, Bonke B, De Haes JCJM. The Multidimensional Fatigue
Inventory (MFI) psychometric qualities of an instrument to assess fatigue. J
Psychosom Res 1995;39:315-25.
28.
Gladman DD, Urowitch MB, Kagal A, Hallet D. Accurately describing changes in
disease activity in systemic lupus erythematosus. J Rheumatol 2000;27:377-9.
29.
Abrahamowicz M, Fortin PR, Du BR, Nayak V, Neville C, Liang MH. The relationship
between disease activity and expert physician's decision to start major treatment in
active systemic lupus erythematosus: a decision aid for development of entry criteria
for clinical trials. J Rheumatol 1998;25:277-84.
30.
Cutolo M, Capellino S, Sulli A, et al. Estrogens and autoimmune diseases. Ann N Y
Acad Sci. 2006;1089:538-47.
31.
Kuratsune H, Yamaguti K, Sawada M, et al. Dehydroepiandrosterone sulfate
deficiency in chronic fatigue syndrome. Int J Mol Med 1998;1:143-6.
52
FATIGUE IN PATIENTS WITH SLE: THE ROLE OF DHEAS
32.
Scott LV, Salahuddin F, Cooney J, Svec F, Dinan TG. Differences in adrenal steroid
profile in chronic fatigue syndrome, in depression and in health. J Affective Disord
1999;54:129-37.
33.
Van Rensburg SJ, Potocnik FCV, Kiss T, et al. Serum concentrations of some metals
and steroids in patients with chronic fatigue syndrome with reference to neurological
and cognitive abnormalities. Brain Res Bull 2001;55:319-25.
34.
Cleare AJ, O'Keane V, Miell JP. Levels of DHEA and DHEAS and responses to CRH
stimulation
and
hydrocortisone
treatment
in
chronic
fatigue
syndrome.
Psychoneuroendocrinology 2004;29:724-32.
35.
Turan T, Izgi HB, Ozsoy S, et al. The effects of galantamine hydrobromide treatment
on dehydroepiandrosterone sulfate and cortisol levels in patients with chronic fatigue
syndrome. Psychiatr Invest 2009;6:204-10.
36.
Heuser I, Deuschle M, Luppa P, Schweiger U, Standhardt H, Weber B. Increased
diurnal plasma concentrations of dehydroepiandrosterone in depressed patients. J
Clin Endocrinol Metab 1998;83:3130-3.
37.
Takebayashi M, Kagaya A, Uchitomi Y, et al. Plasma dehydroepiandrosterone sulfate
in unipolar major depression. J Neural Transm 1998;105:537-42.
38.
Sonnenschein M, Mommersteeg PMC, Houtveen JH, Sorbi MJ, Schaufeli WB, van
Doornen LJP. Exhaustion and endocrine functioning in clinical burnout: An in-depth
study using the experience sampling method. Biol Psychol 2007;75:176-84.
39.
Köller MD, Templ E, Riedl M, et al. Pituitary function in patients with newly diagnosed
untreated systemic lupus erythematosus. Ann Rheum Dis 2004;63:1677-80.
40.
Gutiérrez MA, Garcia ME, Rodriguez JA, Rivero S, Jacobelli S. Hypothalamic-pituitaryadrenal axis function and prolactin secretion in systemic lupus erythematosus. Lupus
1998;7:404-8.
41.
Van der Goes MC, Bossema ER, Hartkamp A, et al. Cortisol during the day in patients
with systemic lupus erythematosus or primary Sjögren's syndrome. J Rheumatol
2011;38:285-8.
42.
Kancheva R, Hill M, Novak Z, Chrasina J, Kancheva L, Starka L. Neuroactive steroids
in periphery and cerebrospinal fluid. Neuroscience 2011;191:22-7.
43.
Straub RH, Lehle K, Herfarth H, et al. Dehydroepiandrosterone in relation to other
adrenal hormones during an acute inflammatory stressful disease state compared
with chronic inflammatory disease: Role of interleukin-6 and tumour necrosis factor.
Eur J Endocrinol 2002;146:365-74.
53
54
Chapter 4
The association of fatigue and
disease activity in patients with
rheumatoid arthritis: a latent
growth curve model analysis of
between-subject differences
and within-subject changes
Cécile L. Overman
Anne C.A. Marijnissen
Jacob M. van Laar
Floris P.J.G. Lafeber
Rinie Geenen
on behalf of investigators of the Society for Rheumatology Research
Utrecht (SRU)
Submitted as:
Overman, C.L., Marijnissen, A.C.A., van Laar, J.M., Lafeber, F.P.J.G.,
Geenen, R. Fatigue and disease activity in patients with rheumatoid
arthritis: a growth curve analysis of between-subject differences and
within-subject changes.
55
CHAPTER 4
ABSTRACT
Background: The lack of association between fatigue and objective
markers of disease activity in patients with rheumatoid arthritis (RA) is
counterintuitive since patients and doctors consider fatigue an indicator
of underlying disease activity. Perhaps within-subject changes in fatigue
caused by changes in disease activity are hidden by stable betweensubject differences in fatigue levels.
Objective: The current study examined if, in contrast to betweensubject differences, within-subject changes in fatigue are associated
with objective indicators of disease activity.
Methods: Consecutive patients with RA (n=248, mean age 53 years,
76% female, 56% rheumatoid factor positive), starting with biological
treatment were monitored at treatment start and three and six months
later. Fatigue was assessed with a visual analogue scale (0-10) and
disease activity with the erythrocyte sedimentation rate and swollen
joint count (28 joints). Latent growth curve model analyses examined
the level and course of fatigue and disease activity, their possible
association, and the possible prediction by patient characteristics.
Results: Across six months, fatigue (small effect size, d = -0.43) and
disease activity (moderate effect size, d = -0.68) improved. Neither
between-subject differences nor within-subject changes of fatigue and
disease
activity
were
associated.
Female
gender,
younger
age,
rheumatoid factor negative and previous use of biologicals predicted a
higher fatigue level, not within-subject change of fatigue.
Conclusion: Our results showed RA fatigue to be a rather stable
individual characteristic that is not a reflection of average or transient
disease activity. This suggests that treatment directed at disease
remission is hardly a means to treat fatigue.
56
ASSOCIATION OF FATIGUE AND DISEASE ACTIVITY IN RA
INTRODUCTION
Fatigue is a prevalent and debilitating problem in rheumatoid arthritis
(RA).1 Although disease activity is likely a precipitating factor of fatigue,
the relation between disease activity and fatigue remains uncertain. To
clarify the association between disease activity and fatigue, it could be
important to make a distinction between enduring aspects of these
variables, as reflected in consistent differences between people, versus
transient, intra-individual changes in these variables.
Inflammation may induce fatigue. Pro-inflammatory cytokines,
besides playing a crucial role in RA inflammation,2 are known to induce a
constellation of non-specific disease symptoms, including fatigue.3 This
causal model suggests that fatigue correlates with the amount of
inflammation. However, previous research showed that fatigue had little
or
no
association
with
the
level
of
inflammation,4-10
which
is
counterintuitive since both patients and doctors regard fatigue as an
indicator of underlying disease activity.11-13
Previous studies of relations between disease activity and fatigue
did not distinguish enduring differences between subjects from transient
changes in these variables. Differences in fatigue levels between
patients are indicated to be associated with gender, pain, physical
functioning, and psychosocial factors12,14,15 but a correlation between
disease activity and fatigue is commonly absent in cross-sectional
designs
examining
between-subject
differences.14
Perhaps
within-
subject variations in fatigue as a consequence of changes in disease
activity are hidden by between-subject differences in fatigue levels. If
this is true than within-subject changes in disease activity and fatigue
are correlated while between-subject differences in disease activity and
fatigue
are
hardly
correlated.
The
current
study
examined
this
hypothesis for objective indicators of disease activity as well as the
association of patient characteristics with between-subject differences
and within-subject changes in fatigue.
MATERIALS AND METHODS
Participants
This study used data of patients who started with biological treatment
and were enrolled in the ongoing observational BIOCURA cohort study
57
CHAPTER 4
between June 2009 and June 2013. All patients had a diagnosis of RA
according to the American College of Rheumatology (ACR) criteria for
RA,16 were aged > 18, received care in one of the Dutch rheumatology
departments collaborating in the Society for Rheumatology Research
Utrecht (SRU), and started with biological treatment. Patients were
excluded from the study when they did not understand the Dutch
language sufficiently to appreciate the informed consent and to
complete the questionnaires. All participating patients gave written
informed consent. The BIOCURA study was conducted according to the
principles of the Declaration of Helsinki 17 and approved by the ethical
review board of the University Medical Centre (UMC) Utrecht.
Assessments
In this study, there were three assessment occasions: at the start of
treatment and three and six months later. At each occasion, patients
completed a diary during one week. Each evening, patients responded to
the question “How fatigued were you today?” on a visual analogue scale
(VAS) ranging from zero “not fatigued at all” to ten “extremely
fatigued”. A single item VAS fatigue has been indicated to be reliable,
has a good sensitivity to change,18 and there is evidence for its validity
to assess fatigue in RA.19
Disease activity was assessed once at each occasion with
measures
that
objectively
reflect
inflammation:
the
erythrocyte
sedimentation rate (ESR) in mm/h (Westergren) and swollen joint count
based on 28 joints (SJC28). Together these measures comprise the
objective domain part of the Disease Activity Score based on 28 joints
(DAS28) which is the most commonly used valid measure in RA to
assess disease activity.20 The two components of the DAS28 score which
also reflect the subjective experience of disease activity - tender joint
count and self-report of general well-being - were not included in this
study because fatigue is also a subjective - self-reported - experience.
Associations observed between subjective disease activity and fatigue
could be due to response tendencies, neuroticism, momentary negative
affect, and other influences leading to spurious correlations between
variables.
58
ASSOCIATION OF FATIGUE AND DISEASE ACTIVITY IN RA
At the start of treatment, demographics (i.e. gender, age,
education level, marital status) and rheumatoid factor status were
collected and amongst other parameters it was also recorded whether or
not it was the first time patients were treated with a biological.
Statistical Analyses
For each assessment week of VAS fatigue scores, a mean VAS fatigue
was calculated per patient and used in analyses; the internal consistency
of these fatigue measures expressed in Cronbach’s alpha varied
from .95 in the week after the start of treatment to .96 and .97, three
and six months later. To get an optimal score distribution, ESR and
SJC28 were transformed into one disease activity score using the
formula of the objective domain part of the DAS28: Objective DAS28 =
0.28 x √(SJC) + 0.70 x ln(ESR).
Intraclass correlation coefficients (ICCs) were calculated to
examine the extent to which fatigue and disease activity varied between
patients and within patients across time.
A step by step latent growth curve model analysis (LGCM) was
used to examine these models: 1) the level and course of fatigue and
disease activity separately, 2) the possible association between the level
and the course of fatigue and disease activity, and 3) patient
characteristics as predictors of the level and course of fatigue and
disease activity. Both VAS fatigue and objective DAS28 scores had small
deviations from a normal distribution on one or two of the three time
points. However, standard model results are reported because they did
not differ from bootstrapped or Bayesian model results. Polynomials
were examined and a quadratic term was found to improve the linear
models and was added to all models.
IBM SPSS Statistics version 22 was used for the descriptive
analyses. The calculation of the ICC and LGCM analyses were done in
Mplus version 7.2.21 All tests were two-sided and p < .05 was
considered significant.
59
CHAPTER 4
Table 1. Baseline characteristics of the 248 patients with RA
189
(76.2)
53.45
(12.67)
Males
55.86
(11.36)
Females
52.70
(12.99)
Low
61
(24.6)
Middle
87
(35.1)
High
66
(26.6)
Unknown
34
(13.7)
Female sex, n (%)
Age, mean (SD)
Education level, n (%)
Marital status, n (%)
20
(8.1)
158
(63.7)
Divorced
22
(8.9)
Widowed
14
(5.6)
Unknown
34
(13.7)
138
(55.6)
Negative
75
(30.2)
Unknown
35
(14.1)
9.44
(9.31)
Yes
144
(58.1)
No
100
(40.3)
4
(1.6)
VAS fatigue, mean (SD)
4.62
(2.36)
Objective DAS28, mean (SD)
4.54
(1.26)
Single
In a relationship
Rheumatoid factor status, n (%)
Positive
Disease duration in years, mean (SD)
First time on biologicals
Unknown
Education level: ‘Low’: Primary school or lower vocational secondary education. ‘Middle’:
Intermediate general secondary education (high school) or intermediate vocational
education. ‘High’: Higher general secondary education (high school), higher vocational
education, or university education. VAS fatigue = Visual Analogue Scale fatigue (‘How
fatigued were you today?’), range: 0 - 10 (not fatigued at all - extremely fatigued).
Objective DAS28 = the objective domain part of the formula of the Disease Activity Score
based on 28 joints: 0.28 x √(Swollen joint count based on 28 joints) + 0.70 x
ln(erythrocyte sedimentation rate).
60
ASSOCIATION OF FATIGUE AND DISEASE ACTIVITY IN RA
RESULTS
Characteristics of the study population
Table 1 shows the characteristics of the 248 consecutive patients with
RA who provided data for this study between June 2009 and June 2013.
Twenty-one patients (8.5%) who participated in clinical measurements
completed neither the baseline questionnaire nor the diaries at home,
thus, they did not disclose their education level or marital status and did
not have fatigue scores. Compared to patients who did complete the
baseline questionnaire and/or diaries, these patients were more often
male (χ2 = 4.60, p = .03); they did not differ on age (t = -0.35, p
= .73), rheumatoid factor (χ2 = 0.00, p = .99), disease duration (MannWhitney U test, p = .55), objective DAS28 score (t = 1.66, p = .10),
and on whether or not it was their first time using biologicals (χ 2 = 0.04,
p = .85). At baseline and after three and six months, 81%, 62%, and
65% of patients were fatigued (VAS fatigue > 2.5) and 44%, 31%, and
30% had high fatigue scores (VAS fatigue > 5.0).
Between- and within-subject variance
The ICC showed that 67% of the variance in fatigue was betweensubject variance, reflecting stable individual differences in fatigue across
six months (ICC = 0.67). The remaining 33% reflected within-subject
variance, which includes patients’ changes in fatigue across time and
error variance. With regard to disease activity, the ICC showed 68%
between-subject variance and 32% within-subject variance and error.
Latent growth curve model 1
The first LGCM analysing fatigue and disease activity separately showed
a significant linear and quadratic improvement over time of both fatigue
and disease activity (Table 2, Model 1). Across six months, the effect
size of the overall improvement was small for fatigue (d = -0.43) and
moderate for disease activity (d = -0.68).
Variance around the quadratic slope could not be estimated and
was fixed at zero (i.e. the quadratic slope was estimated not to vary
between patients). Variances around the intercept and linear slope,
however, could be estimated. There was significant variance around the
intercept for both fatigue and disease activity indicating that patients
61
CHAPTER 4
significantly differed in both fatigue and disease activity levels. For
disease activity, variance around the linear slope was significant
indicating that the course of disease activity differed between patients.
However, the linear course of fatigue did not differ significantly between
patients.
Latent growth curve model 2
In the second LGCM, fatigue and disease activity were both included in
the model. Results revealed no association between the intercepts and
slopes of fatigue and disease activity. This means that neither betweensubject levels of fatigue and disease activity nor within-subject changes
in fatigue and disease activity across six months were associated (Table
2, Model 2).
Latent growth curve model 3
In the third and final LGCM, patient characteristics were included in the
model as predictors of the intercept and slope of fatigue and disease
activity. After backward exclusion, education level, marital status, and
disease duration were removed (p > .17) while gender, age, rheumatoid
factor (RF), and whether or not patients used a biological before this
study remained in the final model as significant predictors.
Levels, not the course of fatigue and disease activity were
predicted by patient characteristics. Therefore, the prediction of slopes
was also removed from the final model (Table 2, Model 3). Analyses
showed that patients were less fatigued when they were of the male
gender, older, had a positive RF, and when they were using biological
medication for the first time. Disease activity was lower for patients who
were younger, had a negative RF, and used biological medication for the
first time. The final model predicted almost one-fifth of the variance of
fatigue (R2 = 0.17) and disease activity (R2 = 0.19) levels.
62
ASSOCIATION OF FATIGUE AND DISEASE ACTIVITY IN RA
Table 2. Results of the Latent Growth curve Model (LGCM) analyses
VAS Fatigue
Model 1
Objective DAS28
a
b
Intercept Mean (SE)
n = 214
4.61 (0.16)***
n = 246
2.34 (0.05)***
Linear slope Mean (SE)
-0.43 (0.10)***
-0.222 (0.03)***
Quadratic slope Mean (SE)
0.05 (0.01)***
0.02 (0.004)***
Intercept Variance (SE)
2.68 (0.62)***
0.47 (0.07)***
ns
Linear slope Variance (SE)
0.04 (0.03)
Quadratic slope Variance (SE)
Fixed at zero
Model 2
0.01 (0.004)**
Fixed at zero
n = 248
c
Correlation between the intercepts (SE)
-0.11 (0.10)ns
Correlation between the slopes (SE)
-0.04 (0.17)ns
Model 3
n = 209
d
Predictors of the intercepts
Gender, B (SE)
0.99 (0.34)**
0.12 (0.11)ns
Age, B (SE)
-0.03 (0.01)*
0.01 (0.004)**
RF, B (SE)
-0.78 (0.31)*
0.30 (0.10)**
First time on biologicals, B (SE)
-0.65 (0.30)*
-0.25 (0.10)**
* = p < .05, ** = p < .01, *** = p < .001, ns = not significant; a = 34 patients did not
fill out diaries, including VAS Fatigue, b = 2 patients did not have DAS28 scores, c = 248
consecutive patients participated in this study and had VAS Fatigue and/or Objective
DAS28 scores, d = 39 patients had missing values on predictors (RF status or first time on
biologicals); VAS fatigue = Visual Analogue Scale fatigue (‘How fatigued were you
today?’), range: 0 - 10 (not fatigued at all – extremely fatigued). Objective DAS28 is the
objective domain part of the formula of the Disease Activity Score based on 28 joints: 0.28
x √(Swollen joint count based on 28 joints) + 0.70 x ln(erythrocyte sedimentation rate);
Model 3 is the final model after backward exclusion of variables and exclusion of the nonsignificant prediction of slopes; Gender (Female = 1); RF = Rheumatoid Factor (positive =
1); First time on biologicals (First time = 1).
DISCUSSION
Neither between-subject differences nor within-subject changes in
disease activity were associated with fatigue. That disease activity was
not associated with individual differences in fatigue was expected.
However, unexpectedly, change in disease activity across the six month
interval was also not found to correlate with change in fatigue during
this interval. Patient characteristics were associated with differences
between patients in the level of fatigue but not with the course of
fatigue within patients.
63
CHAPTER 4
While fatigue within patients changed over time, changes were
small. Our results showed that fatigue is more a stable individual
characteristic than a transient state caused by current disease activity.
Two-third of the variation in fatigue could be ascribed to enduring
individual differences. These results are in agreement with previous
research showing that fatigue levels are rather stable over time in many
patients with RA12,15 and unrelated to disease activity. While current
disease activity seems to be unrelated to both the level and change in
fatigue, it is possible that past disease activity does play a role in setting
the overall level of future fatigue. Research shows that already the first
disease flare-up and the associated increase in pro-inflammatory
cytokines2,3 may result in neurological changes which may underlie
fatigue and its dimensions including reduced behavioural motivation and
flexibility, and uncertainty about usefulness of actions.22
The reduction in fatigue was small but significant. Since the
reduction in fatigue by lack of association could not have been mediated
by the reduction in disease activity and biologicals specifically target
pro-inflammatory
cytokines
which
are
known
mediators
of
the
3
experience of feeling sick, including fatigue, the possibility exists that
blockade of pro-inflammatory cytokines directly triggered the reduction
in fatigue. To confirm this possibility, future research should use a RCT
design to compare the improvement in fatigue in patients whose disease
activity is not improved between patients receiving a biological and
patients receiving placebo.
The between-subject differences in the level of fatigue were
associated with several patient characteristics. This may imply that
fatigue can likely improve most by interventions directed at improving
more
stable
patient
characteristics
like
health
behaviour
and
psychosocial status rather than by pharmacological interventions aimed
at reducing acute disease activity. Patient education has shown promise
in improving patients’ health behaviour and fatigue.23 Also psychological
interventions
such
as
cognitive
behavioural
therapy
have
been
24
successful in reducing fatigue.
Our study was an observational study using data from patients
treated with biologicals according to daily clinical practice. Being an
observational study, our sample is a better reflection of the general RA
64
ASSOCIATION OF FATIGUE AND DISEASE ACTIVITY IN RA
population treated with biologicals than patients selected on stringent
criteria in randomized clinical trials (RCTs). Our patient sample had
starting levels of fatigue comparable to other patient cohort samples
assessed with a VAS fatigue scale.5 However, while observational
studies with their more diverse patient samples25,26 may have more
variance on outcome variables between patients, they are also known to
show less improvement on outcome variables than RCTs,26 limiting the
variance on outcome variables within patients. Even though our sample
consisted of less “ideal” patients, the overall small reduction in fatigue
over time was similar to the mean reduction in fatigue found in patient
samples treated with biologicals and methotrexate compared to patients
treated with placebo and methotrexate in an RCT.27 The sample size of
our study in combination with the only small to moderate improvements
in fatigue and disease activity, may have limited the power of the LGCM
models. While visual observation of the data showed both patients with
negative and patients with positive quadratic curves for fatigue and
disease activity, our models could not estimate this variance. Therefore,
our possibility to find an association between the course (i.e. variance)
of fatigue and disease activity and to predict both courses may have
been limited by our observational study design.
Our study was the first to examine fatigue and associating factors
while disentangling between-subject differences and within-subject
change in fatigue and objective indicators of disease activity. This study
adds to the evidence that fatigue and disease activity are not related in
patients with RA. Between-subject differences in fatigue in RA reflect
mostly enduring differences between patients and are predicted by
stable person-bound characteristics, not by disease activity. Our study
indicated that the change in fatigue within patients over time is small
and does not reflect the underlying inflammatory process. Because of its
impact on patients’ quality of life,23 fatigue should be assessed in clinical
practice and research. To target chronic fatigue, behavioural and lifestyle
education
and
interventions
are
recommended.23,24
Pharmacological treatment to combat disease flare-ups is not a means
to treat fatigue although some benefit may be expected.
65
CHAPTER 4
ACKNOWLEDGEMENTS
The authors would like to thank Rens van de Schoot, PhD, for his
assistance
with
the
statistical
analyses,
the
patients
for
their
participation, and the rheumatologists and research nurses of the SRU
for their help in data collection.
The Society for Rheumatology Research Utrecht (SRU) consists
of:
University Medical Center Utrecht, dr. J. Tekstra;
Antonius Hospital Nieuwegein/ Utrecht, dr. E.J. ter Borg;
Diakonessen Hospital Utrecht, drs. Y. Schenk;
Meander Medical Center Amersfoort, dr. S. Linn-Rasker;
Sint Maartenskliniek Woerden, dr. W.H. van der Laan;
Hospital St. Jansdal Harderwijk, drs. D.G. Kuipers-Geertsma;
Tergooi Hospital Hilversum, dr. M. Nabibux;
Flevo Hospital Almere, dr. C.M. Verhoef.
REFERENCES
1.
Kirwan JR, Minnock P, Adebajo A, et al. Patient perspective: fatigue as a
recommended
patient
centered
outcome
measure
in
rheumatoid
arthritis.
J
Rheumatol 2007;34:1174-7.
2.
McInnes IB, Schett G. Cytokines in the pathogenesis of rheumatoid arthritis. Nat Rev
Immunol 2007;7:429-42.
3.
Dantzer R. Cytokine-induced sickness behavior: where do we stand? Brain Behav
Immun 2001;15:7–24.
4.
Wolfe F, Hawley DJ, Wilson K. The prevalence and meaning of fatigue in rheumatic
disease. J Rheumatol 1996;23:1407–17.
5.
Pollard LC, Choy EH, Gonzalez J, Khoshaba B, Scott DL. Fatigue in rheumatoid
arthritis reflects pain, not disease activity. Rheumatology (Oxford) 2006;45:885-9.
6.
Bergman MJ, Shahouri SS, Shaver TS, et al. Is fatigue an inflammatory variable in
rheumatoid arthritis (RA)? Analyses of fatigue in RA, osteoarthritis, and fibromyalgia.
J Rheumatol 2009;36:2788-94.
7.
Van Hoogmoed D, Fransen J, Bleijenberg G, van Riel P. Physical and psychosocial
correlates
of
severe
fatigue
in
rheumatoid
arthritis.
Rheumatology
(Oxford)
2010;49:1294-1302.
8.
Stebbings S, Herbison P, Doyle TC, Treharne GJ, Highton J. A comparison of fatigue
correlates in rheumatoid arthritis and osteoarthritis: disparity in associations with
disability, anxiety and sleep disturbance. Rheumatology (Oxford) 2010;49:361–7.
66
ASSOCIATION OF FATIGUE AND DISEASE ACTIVITY IN RA
9.
Campbell RCJ, Batley M, Hammond A, Fowiza I, Kingsley G, Scott DL. The impact of
disease activity, pain, disability and treatments on fatigue in established rheumatoid
arthritis. Clin Rheumatol 2012;31:717-22.
10.
Minnock P, McKee G, Bresnihan B, FitzGerald O, Veale DJ. How much is fatigue
explained by standard clinical characteristics of disease activity in patients with
inflammatory arthritis? A longitudinal study. Arthritis Car Res 2014;66:1597-1603.
11.
Crosby LJ. Factors which contribute to fatigue associated with rheumatoid arthritis. J
Adv Nurs 1991;16:974-81.
12.
Repping-Wuts JWJ, Fransen J, van Achterberg T, Bleijenberg G, van Riel P. Persistent
severe fatigue in patients with Rheumatoid Arthritis. J Clin Nurs 2007;16:377-83.
13.
Rasker JJ. The enigma of fatigue. J Rheumatol 2009;36:2630-2.
14.
Nikolaus S, Bode C, Taal E, van de Laar AFJ. Fatigue and factors related to fatigue in
rheumatoid arthritis: a systematic review. Arthritis Car Res 2013;65:1128-46.
15.
Mancuso CA, Rincon M, Sayles W, Paget SA. Psychosocial variables and fatigue: a
longitudinal study comparing individuals with rheumatoid arthritis and healthy
controls. J Rheumatol 2006 ;33:1496-1502.
16.
Arnett FC, Edworthy SM, Bloch DA, et al. The American Rheumatism Association 1987
revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum
1988;31:315-24.
17.
World Medical Association (WMA). Declaration of Helsinki. Seoul: WMA, October
2008.
http://www.wma.net/en/20activities/10ethics/10helsinki/index.html
(last
accessed 2013 November 8).
18.
Wolfe F. Fatigue assessments in rheumatoid arthritis: comparative performance of
visual analog scales and longer fatigue questionnaires in 7760 patients. J Rheumatol
2004;31:10.
19.
Hewlett S, Hehir M, Kirwan JR. Measuring fatigue in rheumatoid arthritis: a
systematic review of scales in use. Arthritis Car Res 2007;57:429-39.
20.
Prevoo ML, van 't Hof MA, Kuper HH, van Leeuwen MA, van de Putte LB, van Riel PL.
Modified disease activity scores that include twenty-eight-joint counts. Development
and validation in a prospective longitudinal study of patients with rheumatoid
arthritis. Arthritis Rheum 1995;38:44-8.
21.
Muthén, L.K. and Muthén, B.O. (1998-2012). Mplus User’s Guide. Seventh Edition.
Los Angeles, CA: Muthén & Muthén.
22.
Dantzer R, Heijnen CJ, Kavelaars A, Laye S, Capuron L. The neuroimmune basis of
fatigue. Trends Neurosci 2014;37:39-46.
23.
Stebbings S, Treharne GJ. Fatigue in rheumatic disease: an overview. Int J Clin
Rheumatol 2010;5:487-502.
24.
Evers AWM, Kraaimaat FW, van Riel PLCM, de Jong AJL. Tailored cognitive-behavioral
therapy in early rheumatoid arthritis for patients at risk: a randomized controlled
trial. Pain 2002;100:141-53.
25.
Wolfe F, Michaud K, DeWitt EM. Why results of clinical trials and observational studies
of
antitumour
necrosis
factor
(anti-TNF)
therapy
differ:
methodological
and
interpretive issues. Ann Rheum Dis 2004;63(Suppl 2):ii13-ii17.
67
CHAPTER 4
26.
Kievit W, Fransen J, Oerlemans AJM, et al. The efficacy of anti-TNF in rheumatoid
arthritis, a comparison between randomised controlled trials and clinical practice. Ann
Rheum Dis 2007;66:1473-8.
27.
Chauffier K, Salliot C, Berenbaum F, Sellam J. Effect of biotherapies on fatigue in
rheumatoid arthritis: a systematic review of the literature and meta-analysis.
Rheumatology (Oxford) 2012;51:60-8.
68
Section 2
Functioning
69
70
Chapter 5
Change of psychological distress
and physical disability in
patients with rheumatoid
arthritis over the last two
decades
Cécile L. Overman
Maud S. Jurgens
Ercolie R. Bossema
Johannes W.G. Jacobs
Johannes W.J. Bijlsma
Rinie Geenen
Published as:
Overman, C.L., Jurgens, M.S., Bossema, E.R., Jacobs, J.W.G., Bijlsma,
J.W.J., & Geenen, R. (2014). Change of psychological distress and
physical disability in patients with rheumatoid arthritis over the last two
decades. Arthritis Care and Research, 66, 671-678.
71
CHAPTER 5
ABSTRACT
Background: During the past decades, a more cautious approach with
respect to prescribing medication and physical exercise progressed
towards evidence-based guidelines regarding the management
of
rheumatoid arthritis (RA). Currently, physical activity and other means
to improve well-being and functioning are encouraged, and the disease
is targeted earlier with more intensive and aggressive pharmacological
treatment.
Objective: The current study examined whether psychological distress
and physical disability in patients with RA reduced over the last two
decades and whether this is explained by a reduction of disease
activity.
Methods: From 1990 to 2011, consecutive patients with RA (N=1151,
age range 17-86 years, 68% female, 62% rheumatoid factor positive)
were monitored at diagnosis and after 3-5 years of treatment (followup). Depressed mood, anxiety, and physical disability were predicted in
multiple linear regression analyses by year of assessment, disease
activity, and patient demographics.
Results: Over the decades, depressed mood (p=.01), anxiety (p=.001),
and physical disability (p=.02) reduced at diagnosis and withintreatment improvement of anxiety (p=.04) and physical disability
(p<.001) increased. Percentages of patients with depressed mood,
anxiety, and physical disability at follow-up changed from 25%, 23%,
and 53%, respectively, two decades ago to 14%, 12%, and 31%,
respectively, currently. After taking account of reduction in disease
activity,
the
decrease
of
physical
disability
remained
significant
(p<.001).
Conclusion: Over the last two decades, psychological distress and
physical disability decreased. This favourable trend might be partly due
to reduced disease activity. The results indicate that patients with RA
have better opportunity to live a valued life currently than 20 years ago.
72
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
INTRODUCTION
Rheumatoid arthritis (RA) imposes a considerable threat to physical
functioning and psychological well-being.1-4 However, over the past
decades, treatment of RA has improved considerably, at least in wealthy
countries,5 with possible positive implications for patients’ quality of life.
Pharmacological treatment strategies have shifted from intensifying
treatment in case of exacerbations to earlier6 and more intensive
treatment,7-10 including combination therapy,11 tight control and treatto-target strategies,12 and biologic agents.13-16 Furthermore, behavioural
recommendations have shifted from advising rest17,18 to recommending
physical activity19 and encouraging patients to live a less restricted life
in order to improve well-being and keep psychological distress at bay.20
In clinical trials, it has been shown that the new treatment strategies are
associated with lower levels of disease activity, improved psychological
well-being, and better physical functioning,8,9,12,19,21 and population
studies showed a decrease of joint deformities over the years.22,23
Over the past 20 years, the enhanced focus on well-being and
functioning and the improved pharmacotherapy may have resulted in a
reduction of psychological distress and physical disability. This has only
been indicated for a shorter time period in studies with few crosssectional cohorts, not extending to recent years.24-28 The aim of the
current study was to examine whether psychological distress and
physical disability decreased over the last two decades and whether this
decrease was associated with a parallel reduction of disease activity.
MATERIALS AND METHODS
Participants
From 1990 to 2011, a total of 1151 patients with recent RA (median 47
patients per year; range 10-104 per year) were repeatedly assessed
from the time of diagnosis until five years thereafter. Patients were
recruited in rheumatology departments in the Netherlands, collaborating
in the Utrecht Rheumatoid Arthritis Cohort study group. They gave
written informed consent to participate in one of several prospective
trials comparing the effectiveness of different drug treatment strategies,
including strategies that were conventional at the time. These studies
were approved by the ethical review boards of the participating
73
CHAPTER 5
hospitals. Details have been described elsewhere.7-9,12 Briefly, inclusion
criteria were a diagnosis of RA according to the American College of
Rheumatology (ACR) criteria for RA,29 disease duration < 1 year, and
age > 16 years. Excluded from the study were patients diagnosed with
psychiatric disorders, co-morbid diseases, problematic drug usage, and
fertile female patients not taking adequate contraceptive measures or
who were pregnant or breastfeeding.
Assessments
Included in this study were assessments at diagnosis and after 4 years.
If no data were available at the fourth follow-up year, data gathered at
the fifth or, if also not available, the third follow-up year were used. This
time frame guaranteed a follow-up period with conventional treatment
of at least one year as most patients participated in 2-year medical
trials. Data at diagnosis were collected from 1990 to 2008. Follow-up
data were acquired from 1993 to 2011.
Psychological distress was assessed with the depressed mood
and anxiety scales of the Impact of Rheumatic diseases on General
health and Lifestyle (IRGL) questionnaire.30,31 The depressed mood scale
(range 0-24) consists of 6 items derived from a questionnaire by Zwart
and Spooren.32 The anxiety scale (range 10-40) consists of 10 items
derived from the Spielberger State-Trait Anxiety Inventory (STAIDY).33,34 Functional status was assessed with the Disability Index of the
Health Assessment Questionnaire (HAQ).35,36 The Disability Index (range
0-3) comprises 20 items representing difficulty in performing activities
in 8 areas of daily living: 1) dressing and grooming, 2) arising, 3)
eating, 4) walking, 5) hygiene, 6) reach, 7) grip, and 8) common daily
activities. Both the items of the IRGL and of the HAQ are scored on a 4point Likert scale with higher scores representing more depressed mood,
a higher level of anxiety, and more disability in daily functioning
respectively. Cut-off scores representing clinically relevant levels were ≥
6 for depressed mood and ≥ 23 for anxiety.31 The cut-off ≥ 1 was used
to reflect a clinical level of physical disability.37,38 Reliability and validity
of the IRGL and the HAQ are satisfactory.30,36,39
Disease activity was assessed with erythrocyte sedimentation
rate (ESR) in mm/hour (Westergren) and the Thompson articular index
74
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
(range 0-534), a weighted score including both swollen and painful
joints.40 The Thompson joint score was adjusted because for 448
patients only the sum of counted swollen and painful finger and toe
joints had been recorded at diagnosis. To calculate a Thompson joint
score for these patients, it was assumed that when for example 3 finger
joints were swollen and 2 finger joints were painful that 2 finger joints
were both swollen and painful. Furthermore, involvement of the big toe
(normally assigned 8 points) could not be inferred for these patients.
Therefore, for all patients 3 points were assigned to any swollen and
painful toe, resulting in an adjusted total score range of 0-524.
Statistical analysis
Established cut-off scores31,37,38 were used to describe the number of
patients with a clinical level of depressed mood, anxiety, and physical
disability across the two decades.
To examine whether psychological distress and physical disability
improved over the past two decades, multiple linear regression analyses
were applied. The variables were entered hierarchically in blocks, using
a fixed order. Dependent variables were IRGL depressed mood, IRGL
anxiety, and the HAQ Disability Index at diagnosis and baseline-adjusted
scores at follow-up. The regression models were built up in three blocks
(models), as described below.
Year of assessment was entered as a predictor in model 1 to
examine time trends over the two decades. Polynomials were tested but
did not improve the fit of a linear model and were not included in final
regression analyses.
ESR and joint score were added in model 2 as possible mediators
of the time trends of psychological distress and physical disability over
the two decades. When analyses showed that both year of assessment
and ESR or joint score significantly predicted psychological distress or
physical disability, and also that year of assessment significantly
predicted ESR or joint score, mediation of the time trends by disease
activity
variables
was
examined
by
calculating
95%
bootstrap
confidence intervals (95% CIs in multiple mediator models based on a
1000 samples).41
75
CHAPTER 5
Age, sex, education level, marital status, and rheumatoid factor
(RF) status were included in model 3 to examine whether the time
trends of psychological distress and physical disability remained after
taking these variables into account. This third step was added to the
regression models when it became clear that the composition of patient
influx at diagnosis and follow-up changed over the years. This was
examined by predicting age, sex, education level, marital status, and RF
status by year of assessment in linear and logistic regression analyses.
For all linear regression analyses, standardized coefficients (β)
are reported to compare the effects of the individual predictors within a
model and the (added) variance explained by each of the models (ΔR2)
to see if adding variables improved the fit of the overall model. Cohen’s
d was used to express the magnitude of change in the dependent
variables over the two decades with values of 0.2, 0.5, and 0.8
representing cut-offs of small, moderate, and large differences. For the
calculation of Cohen’s d, model estimates of mean values and overall
standard deviations were used. For the logistic regression analyses,
odds ratios (ORs), and goodness of fit of the models (Nagelkerke’s R2)
are reported. In all analyses, significance levels were set at p < .05.
Data were analyzed using SPSS 20.
RESULTS
Characteristics of the study population
The characteristics of the patients are shown in Table 1. Of the 1151
patients, 1060 patients provided the necessary data at diagnosis and
768 patients provided data at both diagnosis and follow-up. Patients
with (n = 292) and without missing data at follow-up did not differ on
characteristics (ps ≥ .07). Patients with missing data at diagnosis (n =
91) were more often male (p = .003) and more often had a middle (p =
.02) or high level of education (p < .001); they did not differ on other
characteristics (ps ≥ .27).
76
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
Table 1. Characteristics of the 1151 patients with RA
Female sex, n (%)
780
(68)
55
(15)
Males
57
(13)
Females
54
(15)
Low
143
(12)
Middle
560
(49)
High
246
(21)
Unknown
202
(18)
Single
111
(10)
Married or cohabiting
827
(72)
Divorced
57
( 5)
Widowed
116
(10)
Unknown
40
( 3)
Positive
715
(62)
Negative
372
(32)
Unknown
64
( 6)
Age, mean (SD)
Education level, n (%)
Marital status, n (%)
Rheumatoid factor status, n (%)
Education level: ‘Low’: Primary school or lower vocational secondary education. ‘Middle’:
Intermediate general secondary education (high school) or intermediate vocational
education. ‘High’: Higher general secondary education (high school), higher vocational
education, or university education.
Figure 1 illustrates the course of improvement across the two
decades
by
showing
the
yearly
percentages
of
patients
with
psychological distress or physical disability at diagnosis and follow-up.
Psychological distress and physical disability were common in our
patient sample and more prevalent at diagnosis than at follow-up. At
diagnosis, the average percentage of patients with depressed mood,
anxiety, or physical disability declined from 43%, 34%, and 64%,
respectively, in 1990-1994 to 32%, 21%, and 60%, respectively, in
2004-2008. At follow-up, these percentages were 25%, 23%, and 53%,
respectively, in 1994-1998 and 14%, 12%, and 31%, respectively, in
2007-2011.
77
CHAPTER 5
78
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
Time trends of psychological distress and physical disability
(model 1)
The results of multiple linear regression analyses at diagnosis are shown
in Table 2. Model 1 shows that, across the two decades, levels of
depressed mood (p = .01), anxiety (p = .001), and physical disability (p
= .02) at diagnosis decreased. The decrease was small for depressed
mood (d = -0.4) and physical disability (d = -0.3) and moderate for
anxiety (d = -0.5).
The baseline-adjusted prediction of psychological distress and
physical disability at follow-up is shown in Table 3. Having entered
values at diagnosis in the first step, now within-treatment change
(instead of absolute follow-up levels) in psychological distress and
physical disability across the two decades was predicted. Model 1 shows
that the within-treatment improvement of anxiety (p = .04) and
physical disability (p < .001), but not of depressed mood (p = .32),
increased across the two decades. This increase in within-treatment
improvement across the decades was small for anxiety (d = -0.2) and
moderate-large for physical disability (d = -0.7).
Mediation of time trends by disease activity (model 2)
At diagnosis, after having taken account of time trends, disease activity
was significantly associated with depressed mood (ΔR2= .02, p = .001),
anxiety (ΔR2= .02, p < .001), and physical disability (ΔR2= .23, p <
.001; Table 2, model 2). To test mediation, we further observed that
ESR (p = .02) and joint score (p = .007) at diagnosis decreased over
the two decades; both decreases were small (d = -0.3 and d = -0.4,
respectively). Bootstrap 95% CIs showed that at diagnosis the decrease
of ESR was a partial mediator of the decrease of depressed mood (95%
CI -0.023, -0.001) and physical disability (95% CI -0.007, -0.001), and
that the decrease of joint score was a partial mediator of the decrease of
anxiety (95% CI -0.032, -0.002) and physical disability (95% CI: 0.007, -0.001).
79
CHAPTER 5
Table 2. Multiple linear regression analyses at diagnosis
Depressed mood
β
MODEL 1
Year
ΔR2
.01*
-.09*
MODEL 2
Year
Anxiety
β
.02**
.11**
.07
.06
.10**
Year
.03***
-.04
.01*
.02***
Joint score
ΔR2
-.08*
-.10**
ESR
MODEL 3
β
.01**
-.12**
-.08*
Physical disability
ΔR2
.23***
-.03
.30***
.28***
.03***
-.07
.04***
.01
ESR
.12**
.08*
.29***
Joint score
.05
.10*
.27***
Age
-.11**
-.11*
.10**
Sex
.09*
.07
.10**
Education level
Middle
-.06
-.07
-.03
High
-.15**
-.10
-.08
Marital status
Married/cohabiting
.07
.01
Divorced/widowed
.12*
.14*
RF status
.02
-.01
.12*
.11*
-.06*
p < .05 = *; p < .01 = **; p < .001 = ***; β = standardized regression coefficient; ΔR2 =
the additional change in the proportion of variance explained by the model compared to
the previous model; the very first ΔR2 is the change in explained variance between model
1 and a model without any predictors; ESR = erythrocyte sedimentation rate; Joint score
= Thompson joint score with an adjusted range of 0-524; Sex with male = 0 and female =
1; Education level was represented by two dummy variables with the lowest level of
education as the reference category; Marital status was represented by two dummy
variables with single status as the reference category; RF status = Rheumatoid factor
status with RF negative status = 0 and RF positive status = 1.
At follow-up, after having taken account of the values at
diagnosis of psychological distress and physical disability and time
trends, disease activity was significantly associated with baselineadjusted depressed mood (ΔR2= .03, p < .001), anxiety (ΔR2= .02, p <
.001), and physical disability (ΔR2= .10, p < .001; Table 3, model 2). To
test mediation, we first observed that ESR (p = .008) and joint score (p
< .001) at follow-up decreased over the two decades. These decreases
were small (d = -0.3) and moderate-large respectively (d = -0.7).
Bootstrap confidence intervals showed that at follow-up the decrease of
ESR was a partial mediator of the baseline-adjusted decrease of physical
80
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
disability (95% CI -.004, -.001) and the decrease of joint score was a
partial mediator of the baseline-adjusted decrease of anxiety (95% CI 0.065, -0.010) and physical disability (95% CI -0.011, -0.004).
Table 3. Baseline-adjusted multiple linear regression analyses at follow-up
Depressed mood
β
MODEL 1
Baseline value
Year
Anxiety
2
ΔR
β
.001
.44***
ΔR
β
.01*
.52***
-.04
MODEL 2
Physical disability
2
.04***
.46***
-.07*
.03***
-.21***
.02***
.51***
.10***
Baseline value
.44***
Year
.001
-.04
-.14***
ESR
.06
.05
.15***
Joint score
.15***
.13***
MODEL 3
.02*
ΔR2
.44***
.24***
.03***
.04***
Baseline value
.42***
.50***
.41***
Year
.05
.01
ESR
.05
.02
.14***
Joint score
.15***
.12***
.24***
Age
.04
.08*
.04
Sex
.07
.08*
.14***
Middle
-.09
-.11*
High
-.15*
-.16**
-.11**
Education level
.05
-.07
Marital status
Married/cohabiting
.02
-.01
.03
Divorced/widowed
.03
-.02
.05
RF status
-.003
.09**
.03
p < .05 = *; p < .01 = **; p < .001 = ***; β = standardized regression coefficient; ΔR2 =
change in the additional proportion of variance explained by the model compared to the
previous model; the very first ΔR2 is the change in explained variance between model 1
and a model with only the baseline value as a predictor; Baseline value = Baseline value of
the dependent variable; ESR = erythrocyte sedimentation rate; Joint score = Thompson
joint score with an adjusted range of 0-524; Sex with male = 0 and female = 1; Education
level was represented by two dummy variables with the lowest level of education as the
reference category; Marital status was represented by two dummy variables with single
status as the reference category; RF status = Rheumatoid factor status with RF negative
status = 0 and RF positive status = 1.
81
CHAPTER 5
Changes in the composition of patient influx (model 3)
In the group of patients which provided data at diagnosis (n = 1060),
age decreased over the two decades (d = -0.40, R2 = .01, β = -.10, p =
.001), the number of patients with a middle or high level of education
increased (Nagelkerke’s R2 = .15, ORs 1.24 and 1.38, respectively, p <
.001), the number of patients with a positive RF status increased
(Nagelkerke’s R2 = .01, OR 1.03, p = .04), and the number of divorced
or widowed patients decreased (Nagelkerke’s R2 = .01, OR 0.92, p =
.005). Other patient characteristics did not change over the years (ps ≥
.26) for this group. In the group of patients which provided data at both
diagnosis and follow-up (n = 768), the number of patients with a middle
or high level of education increased (Nagelkerke’s R2 = .15, ORs 1.23
and 1.37, respectively, p < .001). No other changes in patient
characteristics were observed across the years for this group (ps ≥ .11).
Model 3 tested whether the time trends of psychological distress
and physical disability were affected by the change in the composition of
patient influx. Patient characteristics were inconsistently associated with
at least one of the psychological distress or physical disability variables
at diagnosis or follow-up. Adding all patient characteristics to the model
eliminated the significance of year of assessment as a predictor of
depressed mood and anxiety at diagnosis (Table 2, model 3), while the
baseline-adjusted follow-up decrease of physical disability as a function
of year of assessment remained significant (Table 3, model 3).
DISCUSSION
The current study in patients with a recent RA diagnosis showed that
psychological distress and physical disability decreased across the last
two decades. Reduction in disease activity partly explained this
decrease. Across the decades, especially the trend of progressively
decreasing physical disability after the first years of treatment was
noteworthy and this favourable trend remained significant after having
taken account of the reduction of disease activity and change in the
composition of patient influx.
Adding to findings from previous studies,24,28 our study examined
whether parallel changes in outcomes were associated. Our study
suggests that the favourable trends of psychological distress and
82
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
physical disability might be caused in part by reduced disease activity.
Both improved pharmacological treatment, as suggested previously23
and improved non-pharmacological management could have induced the
favourable trends of psychological distress and physical disability
observed after the first years of treatment by reducing disease activity
across the last two decades.
Improved treatment strategies could have affected psychological
distress and physical disability by reducing disease activity, but also by
other mechanisms. Targeted non-pharmacological therapies in small
samples have shown positive effects of exercise therapy19 and cognitive
behavioural therapy,42 but much more important in the large population
of patients with a recent RA diagnosis might have been the changed
education
by rheumatologists and
health professionals enhancing
physical activity and encouraging patients to live a valued life.20
Furthermore, since pro-inflammatory cytokines may have behavioural
effects,43,44 the blocking of these cytokines with biologic agents in recent
years may have caused a reduction of psychological distress and
physical disability not fully explained by reduced disease activity.
The improvements of psychological distress, physical disability
and reduced disease activity at diagnosis cannot be ascribed to
improved treatment strategies. These improvements might be due to
earlier diagnosis over the years6 as suggested in our study by a
decrease in age at time of diagnosis across the past 20 years.
Patient characteristics changed across the years in our patient
sample. The observed increase in education level during the past 20
years is not specific for our patient sample, but has also been found in
the general population,45,46 accompanied by an increase of socioeconomic status46 and life-expectancy.47 When adjusting for historic
trends in analysis, as we did for education level, it is impossible to
ascertain whether these trends play a causal role in the observed
psychological and functional improvements across the decades, or
whether they only reflect a historic change occurring simultaneously,
affecting the improvements statistically but not in real life. In any case,
our observed trend of progressively decreasing physical disability after
the first years of treatment remained significant after correction for
historic changes in patient characteristics.
83
CHAPTER 5
Improved treatment strategies have shown to be capable of
improving patients’ psychological well-being and physical functioning in
randomized controlled trials.8,9,12,19,21 Therefore, treatment improving
over the decades is a likely candidate to explain, at least in part, the
improvement in psychological well-being and physical functioning.
However, our statistical tests do not give a final answer. It cannot be
excluded that trends of improving treatment, decreasing disease
activity, and increasing well-being and functioning are merely parallel
occurrences without the existence of a causal connection.
The decrease of psychological distress over the decades was not
as pronounced as the decrease of physical disability. However, our
finding that mood and anxiety improved across the decades, even with
small effect sizes, is remarkable when taking into consideration that in
the past decades psychological distress increased instead of decreased
in the general population.48
The current study has strengths that add to previous findings.2328,37,49
It is one of few population studies25-28 examining time trends of
both physical functioning and psychological well-being, and the first to
examine reduced disease activity as a possible mediator of these time
trends. Moreover, time trends were examined with annual cohorts over
a long period of time (21 years), adding to findings of population studies
based on a more limited number of cross-sectional cohorts and covering
fewer years.25-28 Also, our patient sample had a uniform disease
duration. Therefore, in contrast with other cross-sectional population
studies,24-27 the effect of year of assessment was not confounded by
disease duration.50 Lastly, our data covered more recent years than
previous population studies.23-28,37,49 Therefore, effects of the newest
treatments were included.
The current study also has limitations. The results do not refer to
specific treatment modalities; all patients received treatment according
to guidelines at that time. Furthermore, our findings do not generalize
beyond patients with a recent RA diagnosis or beyond wealthy countries
since the clinical burden of RA is still especially substantial in less
prosperous countries.5 Lastly, it was not possible to definitively establish
reduced disease activity as a cause of reduced psychological distress
and physical disability or to examine prediction or confounding of the
84
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
results by patient characteristics that changed over the decades, such as
increased level of education, which is a limitation inherent to the type of
study design.
In conclusion, in this population of patients with a recent RA
diagnosis,
psychological
distress
and
physical
disability
reduced
significantly over the last two decades. This favourable trend might be
partly due to a decrease in disease activity. The research findings
indicate that it is easier to live a valued life while having RA currently
than 20 years ago.
ACKNOWLEDGEMENTS
The authors thank all participating rheumatologists and research nurses
of the Society for Rheumatology Research Utrecht (SRU) for their help in
data collection.
REFERENCES
1.
Dickens C, McGowan L, Clark-Carter D, Creed F. Depression in rheumatoid arthritis: a
systematic review of the literature with meta-analysis. Psychosom Med 2002;64:52–
60.
2.
VanDyke MM, Parker JC, Smarr KL, et al. Anxiety in rheumatoid arthritis. Arthritis
Rheum 2004;51:408–12.
3.
Isik A, Koca SS, Ozturk A, Mermi O. Anxiety and depression in patients with
rheumatoid arthritis. Clin Rheumatol 2007;26:872–8.
4.
Overman CL, Bossema ER, van Middendorp H, et al. The prospective association
between psychological distress and disease activity in rheumatoid arthritis: a
multilevel regression analysis. Ann Rheum Dis 2012;71:192-7.
5.
Sokka T, Kautiainen H, Pincus T, et al. Disparities in rheumatoid arthritis disease
activity according to gross domestic product in 25 countries in the QUEST–RA
database. Ann Rheum Dis 2009;68:1666–72.
6.
Emery P, Breedveld FC, Dougados M, Kalden JR, Schiff MH, Smolen JS. Early referral
recommendation
for
newly
diagnosed
rheumatoid
arthritis:
evidence
based
development of a clinical guide. Ann Rheum Dis 2002;61:290–7.
7.
Van der Heide A, Jacobs JWG, Bijlsma JWJ, et al. The Effectiveness of Early
Treatment with “Second-Line” Antirheumatic Drugs: A Randomized, Controlled Trial.
Ann Intern Med 1996;124:699-707.
8.
Verstappen SMM, Jacobs JWG, Bijlsma JWJ, et al. Five-year follow-up of rheumatoid
arthritis patients after early treatment with disease-modifying antirheumatic drugs
versus treatment according to the pyramid approach in the first year. Arthritis Rheum
2003;48:1797–1807.
9.
Verstappen SMM, Jacobs JWG, Van der Veen MJ, et al. Intensive treatment with
methotrexate in early rheumatoid arthritis: aiming for remission. Computer Assisted
85
CHAPTER 5
Management in Early Rheumatoid Arthritis (CAMERA, an open-label strategy trial).
Ann Rheum Dis 2007;66:1443-9.
10.
Jurgens MS, Welsing PMJ, Jacobs JWG. Overview and analysis of treat-to-target trials
in rheumatoid arthritis reporting on remission. Clin Exp Rheumatol 2012;30:S56-63.
11.
Boers M, Verhoeven AC, Markusse HM, et al. Randomised comparison of combined
step-down prednisolone, methotrexate and sulphasalazine with sulphasalazine alone
in early rheumatoid arthritis. Lancet 1997;350:309-18.
12.
Bakker MF, Jacobs JWG, Welsing PMJ, et al. Low-dose prednisone inclusion in a
methotrexate-based,
tight
control
strategy
for
early
rheumatoid
arthritis:
a
randomized trial. Ann Intern Med 2012;156:329-39.
13.
Furst D, Breedveld F, Kalden J, et al. Updated consensus statement on biological
agents, specifically tumour necrosis factor α (TNFα) blocking agents and interleukin-1
receptor antagonist (IL-1ra), for the treatment of rheumatic diseases, 2005. Ann
Rheum Dis 2005;64:iv2–iv14.
14.
Smolen JS, Boers M, Abadie EC, et al. Recommendations for an update of 2003
European regulatory requirements for registration of drugs to be used in the
treatment of RA. Curr Med Res Opin 2011;27:315-25.
15.
Jung YO, Kim HA. Recent Paradigm Shifts in the Diagnosis and Treatment of
Rheumatoid Arthritis. Korean J Intern Med 2012;27:378-87.
16.
Sharma P, Pathak K. Are biological targets the final goal for rheumatoid arthritis
therapy? Expert Opin Biol Ther 2012;12:1611-22.
17.
Smith RD, Polley HF. Rest therapy for rheumatoid arthritis. Mayo Clin Proc
1978;53:141–5.
18.
De Ridder D, Geenen R, Kuijer R, Van Middendorp H. Psychological adjustment to
chronic disease. Lancet 2008;372:246–55.
19.
De Jong Z, Munneke M, Zwinderman AH, et al. Is a long-term high-intensity exercise
program effective and safe in patients with rheumatoid arthritis? Results of a
randomized controlled trial. Arthritis Rheum 2003;48:2415–24.
20.
Geenen R, Mulligan K, Shipley M, Newman S. Psychosocial dimensions of the
rheumatic diseases. In: Bijlsma JWJ, Burmeister GR, da Silva JAP, Faarvang KL,
Hachulla E & Mariette X, editors. EULAR Compendium on Rheumatic Diseases.
London: BMJ Publishing Group; 2009. p. 635-650.
21.
Singh JA, Christensen R, Wells GA, et al. A network meta-analysis of randomized
controlled trials of biologics for rheumatoid arthritis: A Cochrane overview.
CMAJ 2009;181:787-96.
22.
Sokka T, Kautiainen H, Hakkinen A, Hannonen P. Radiographic progression is getting
milder in patients with early rheumatoid arthritis. Results of 3 cohorts over 5 years. J
Rheumatol 2004;31:1073–82.
23.
Finckh A, Choi HK, Wolfe F. Progression of radiographic joint damage in different
eras: trends towards milder disease in rheumatoid arthritis are attributable to
improved treatment. Ann Rheum Dis 2006;65:1192–7.
24.
Pincus T, Sokka T, Kautiainen H. Patients seen for standard rheumatoid arthritis care
have significantly better articular, radiographic, laboratory, and functional status in
2000 than in 1985. Arthritis Rheum 2005;52:1009–19.
86
TWO DECADES OF PSYCHOLOGICAL AND PHYSICAL HEALTH IMPROVEMENT IN RA
25.
Heiberg T, Kvien TK, Uhlig T, FA. Seven year changes in health status and priorities
for improvement of health in patients with rheumatoid arthritis. Ann Rheum Dis
2005;64:191–5.
26.
Söderlin MK, Lindroth Y, Jacobsson LTH. Trends in medication and health-related
quality of life in a population-based rheumatoid arthritis register in Malmö, Sweden.
Rheumatology (Oxford) 2007;46:1355–8.
27.
Uhlig T, Heiberg T, Mowinckel P, Kvien TK. Rheumatoid arthritis is milder in the new
millennium: health status in RA patients 1994–2004. Ann Rheum Dis 2008;67:1710–
5.
28.
Söderlin MK, Lindroth Y, Turesson C, Jacobsson LTH. A more active treatment has
profound effects on the health status of rheumatoid arthritis (RA) patients: results
from a population-based RA register in Malmö, Sweden, 1997–2005. Scand J
Rheumatol 2010;39:206–11.
29.
Arnett FC, Edworthy SM, Bloch DA, et al. The American Rheumatism Association 1987
revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum
1988;31:315–24.
30.
Huiskes CJAE, Kraaimaat FW, Bijlsma JWJ. Measuring health status in rheumatoid
arthritis: development and refinement of a Dutch health status instrument. Gedrag
en Gezondheid 1990;18:78-89.
31
Huiskes CJAE, Kraaimaat FW, Bijlsma JWJ. IRGL: Invloed van Reuma op Gezondheid
en Leefwijze zelfbeoordelingslijst (IRGL: Impact of Arthritis on Health and Lifestyle
self-report
questionnaire).
Nijmegen:
University
Medical
Center
St.
Radboud
Nijmegen 2004.
32.
Zwart F, Spooren J. Ontwikkeling van een zelfbeoordelingsvragenlijst voor depressie
(Development of a self-report questionnaire for depression). Utrecht: University
Medical Center Utrecht 1982.
33.
Spielberger CD, Gorsuch RL, Lushene RE. Manual of the State-Trait Anxiety
Inventory. Palo Alto, CA: Consulting Psychologists Press 1970.
34.
Van
der
Ploeg
HM,
Defares
PB,
Spielberger
CD.
Handleiding
bij
de
ZelfBeoordelingsVragenlijst ZBV. Lisse: Swets & Zeitlinger 1980.
35.
Fries JF, Spitz PW, Young DY. The dimensions of health outcomes: the Health
Assessment Questionnaire, disability and pain scales. J Rheumatol 1982;9:789-93.
36.
Bijlsma JWJ, Oude Heuvel CH, Zaalberg A. Development and validation of the Dutch
questionnaire capacities of daily life (VDF) for patients with rheumatoid arthritis. J of
Rehab Sciences 1990;3:71-4.
37.
Krishnan E, Fries JF. Reduction in long-term functional disability in rheumatoid
arthritis from 1977 to 1998: a longitudinal study of 3035 patients. Am J Med
2003;115:371–6.
38.
Krishnan E, Sokka T, Hakkinen A, Hubert H, Hannonen P. Normative values for the
Health Assessment Questionnaire disability index: benchmarking disability in the
general population. Arthritis Rheum 2004;50:953–60.
39.
Van Leeuwen MA, Van der Heijde DM, Van Rijswijk MH, et al. Interrelationship of
outcome measures and process variables in early rheumatoid arthritis. A comparison
of radiologic damage, physical disability, joint counts, and acute phase reactants. J
Rheumatology 1994;21:425-9.
87
CHAPTER 5
40.
Thompson PW, Silman AJ, Kirwan JR, Currey HL. Articular indices of joint
inflammation in rheumatoid arthritis. Correlation with the acute-phase response.
Arthritis Rheum 1987;30:618-23.
41.
Preacher KJ, Hayes, AF. Asymptotic and resampling strategies for assessing and
comparing indirect effects in multiple mediator models. Behavior Research Methods
2008; 40:879-91.
42.
Evers AW, Zautra A, Thieme K. Stress and resilience in rheumatic diseases: a review
and glimpse into the future. Nat Rev Rheumatol 2011;7:409-15.
43.
Dantzer R. Cytokine-induced sickness behavior: mechanisms and implications. Ann
NY Acad Sci 2001;933:222–34.
44.
Capuron L, Gumnick JF, Musselman DL, et al. Neurobehavioral effects of interferonalpha in cancer patients: phenomenology and paroxetine responsiveness of symptom
dimensions. Neuropsychopharmacology 2002;26:643–52.
45.
Beets G, van Nimwegen N. Population issues in the Netherlands. Review of Population
and Social Policy 2000;9:87–117.
46.
OECD
(2012),
Education
at
a
Glance
2012:
Highlights,
OECD
Publishing.
http://dx.doi.org/10.1787/eag_highlights-2012-en.
47.
Veenhoven R. Is life getting better? European Psychologist 2005;10:330–343.
48.
Twenge JM. The age of anxiety? The birth cohort change in anxiety and neuroticism,
1952–1993. J Pers Soc Psychol 2000;79:1007–21.
49.
Welsing PM, Fransen J, van Riel PL. Is the disease course of rheumatoid arthritis
becoming milder? Time trends since 1985 in an inception cohort of early rheumatoid
arthritis. Arthritis Rheum 2005;52:2616–24.
50.
Boonen A, Landewe R. Health status in rheumatoid arthritis over 7 years. Ann Rheum
Dis 2005;64:173–5.
88
Chapter 6
Contribution of the subjective
components of the Disease
Activity Score to the response to
Biological Treatment in
Rheumatoid Arthritis
Maud S. Jurgens
Cécile L. Overman
Johannes W.G. Jacobs
Rinie Geenen
Bart V.J. Cuppen
Anne C.A. Marijnissen
Johannes W.J. Bijlsma
Paco M.J. Welsing
Floris P.J.G. Lafeber
Jacob M. van Laar
on behalf of investigators of the Society for Rheumatology Research
Utrecht (SRU)
Published as:
Jurgens, M.S., Overman, C.L., Jacobs, J.W.G., Geenen, R., Cuppen, B.V.J.,
Marijnissen, A.C.A., Bijlsma, J.W.J., Welsing, P.M.J., Lafeber, F.P.J.G., Van Laar,
J.M. Contribution of the subjective components of the Disease Activity Score to
the response to biological treatment in rheumatoid arthritis. Arthritis Care and
Research 10 december 2014, Epub ahead of print.
89
CHAPTER 6
ABSTRACT
Background: A significant proportion of patients with rheumatoid
arthritis do not respond adequately to biological
treatment. We
hypothesized that lack of response to (biological) disease-modifying
anti-rheumatic drug (DMARD) is high in patients in whom the subjective,
patient-reported, component of the Disease Activity Score 28 (DAS28) is
high at baseline.
Objective: The primary aim of our present study was to investigate the
contribution of the more subjective versus the objective components of
the DAS28 to response to biologicals in RA patients as well as the
changes in this contribution over time. The secondary aim was to
examine if the value of this subjective contribution at baseline affects
the response to treatment.
Methods: The DAS28-P was calculated (subjective components of
DAS28 relative to the total DAS28). Patients were derived from the
computer-assisted management in early rheumatoid arthritis (CAMERA)
trial-II and the Biologicals and Outcome Compared and Predicted in
Utrecht region in Rheumatoid Arthritis (BiOCURA) study. Ordinal logistic
and multivariate linear regression analyses were performed.
Results: The DAS28-P score at baseline was not associated with level of
response according to European League against Rheumatism (EULAR)
criteria at three months. Overall, a significant reduction in the DAS28-P
score was observed three months after start of treatment showing a
greater reduction of the combined subjective components in good
responders.
Conclusions: The results reject the hypothesis that the lack of response
to biological DMARDs is especially high in patients in whom the patientreported component of the DAS28 is high at baseline: these subjective
components are not linked to treatment response.
90
DAS28-P AND THE RESPONSE TO BIOLOGICAL TREATMENT
INTRODUCTION
Treatment of RA has significantly improved by concepts such as ‘tight
control’ and ‘treat to target’ as well as the introduction of biological
drugs. Nowadays patients can not only use synthetic disease modifying
anti-rheumatic drugs (DMARDs) - preferably in a treatment strategy
with dose and medication adjustments tailored to the individual patient 1
- but also biological DMARDs increasing the chance of reaching
remission.2,3 However, biological DMARDs are not always effective.4 A
reason could be that RA is probably the final common pathway for
multiple mutually related pathological processes. It is therefore unlikely
to be cured by a single treatment strategy. Individualized approaches
are needed, propagated nowadays as an important next step in further
improving treatment strategies for RA.3
Disease activity measures facilitate clinical decision making. 5 The
most commonly used measure in RA to assess disease activity is
the
6
This
DAS28, a Disease Activity Score based on 28 joints (DAS28).
composite clinical index is calculated by an algorithm of a value for two
more subjective components, the tender joint count (TJC28) and the
visual analogue scale general well-being (VAS-GH), and a value for two
more objective components, the swollen joint count (SJC28) and the
erythrocyte sedimentation rate (ESR). Although the DAS28 was only
validated on group level,6 this clinical score has been used widely to
adjust the treatment of individual patients.7-9 When disease activity is
measured through a – partly – symptom based score like the DAS28,
not all components may respond similarly to treatment. The more
subjective components may be experienced differently by different
patients and this may vary over the disease course within a patient. 10
The subjective components could also be influenced by co-morbidities
(like fibromyalgia, stress, depression, outcome expectations, etc.). The
high pain and disability scores seen in fibromyalgic RA suggest that
these patients
have high scores using summative assessments.11 If
disease activity scores are disproportionately high in relation to the level
of inflammatory synovitis in fibromyalgic RA, the value of disease
activity assessments in these patients is questionable. 11,12 Patients
might still benefit from medication but the effect on disease activity
might be limited.
91
CHAPTER 6
In clinical trials and daily practice a significant proportion of RA
patients do not respond satisfactorily to their biological treatment. We
hypothesized that RA patients with higher relative scores of TJC28 +
VAS-GH have a higher probability of not responding to biological
treatment in comparison to the patients with more inflammatory disease
activity as measured
by SJC28
+
ESR)
and
therefore have
a
disproportionate contribution to the lack of response. Ideally one would
like to predict the response to biological treatment before expectations
and cost are being raised.
The primary aim of our present study was to investigate the
contribution of the more subjective versus the objective components of
the DAS28 to response to biologicals in RA patients as well as the
changes in this contribution over time. The secondary aim was to find
out if the value of this subjective contribution at baseline affects the
response to treatment.
PATIENTS AND METHODS
CAMERA trial-II and BiOCURA study
Patients included in this study were selected from two databases of the
Society for Rheumatology Research Utrecht (SRU), one resulting from
the ‘Computer Assisted Management in Early Rheumatoid Arthritis trialII’ (CAMERA-II) and one from the observational ‘BiOCURA’ study. These
studies were approved by the ethical review boards of the participating
hospitals. All patients had a diagnosis of RA according to the American
College of Rheumatology (ACR) criteria for RA13 and gave written
informed consent. Patients who started with their first biological and
who had DAS28 data available both at baseline (time of starting
biological treatment) and at 3-month follow-up were included in this
study (n=172).
In the CAMERA-II trial, early RA patients were included between
2003 and 2008. Details of the CAMERA-II trial are reported elsewhere.14
In short, this trial compared the addition of 10 mg/d of prednisone or
prednisone-placebo to a randomized, double-blind, prospective, multicentre two-year MTX-based tight-controlled treatment strategy, aiming
for remission. All consecutive patients who visited the outpatient clinic of
one of the 7 SRU rheumatology departments were asked to participate
92
DAS28-P AND THE RESPONSE TO BIOLOGICAL TREATMENT
and the 236 included patients all gave written informed consent. This
strategy included a final step of adding a biological, that step was taken
in 16 (of 117) patients receiving additional prednisone and 42 (of 119)
patients receiving the additional prednisone-placebo. Out of these, 51
participants met the inclusion criteria of the present study. All 51
participants received adalimumab according to standard clinical practice
guidelines.
In the ongoing observational BiOCURA cohort study, conducted
by SRU centres, the first patient was enrolled in June 2009. This study
aims to define (and in the future implement) recommendations and
limitations for the use of each biological agent on the market for
treatment of RA, based on disease activity response to treatment via the
clinical and immunological profile of an individual patient. Every patient
with RA who started a biological could enter (and re-enter after a switch
to another biological) this study, before the first dosage of the biological.
As of July 2013, 121 patients met the inclusion criteria of the present
study (including start with first biological) and were included in the
present analysis. Of these 121 patients the number of biological
DMARDs were mainly TNF-α-blockers and they were distributed as
follows: 52 patients received adalimumab, 43 received etanercept, 10
received golimumab, 6 received infliximab and 3 certolizumab pegol; all
dosages per dutch standardized protocol. Seven patients did not receive
a TNF-blocker: 5 received tocilizumab (IL-6 blocker) en 2 received
rituximab (destroys B cells) per protocol.
Statistical analysis
Descriptive statistics (mean with SD, median with interquartile range, n
with percentage) were used to quantitatively summarize the distribution
of the variables at baseline. Group differences between the two
selections from the study populations in means for continuous data were
tested for significance using independent t-tests or Mann Whitney U if
not normally distributed. For differences in categorical data, Chi-square
tests were performed. Response to therapy of patients was defined
according
the
responders.
15,16
EULAR
criteria
for
good,
moderate,
and
non-
93
CHAPTER 6
To quantify the size of the contribution of the subjective patientreported domains of the DAS28 (TJC28 and VAS) relative to the total
DAS28 a quantity (from here on called “DAS28-P”) derived from the
standard formula to calculate the DAS28 was calculated at baseline and
at three months (Box 1).10 Our null hypothesis stated that the DAS28-P
score at the start is not significantly different between patients with
different levels of response (i.e. good-, moderate-, non-response).
Paired t-tests were performed to see if there is a significant difference
(change) between the DAS28-P score at baseline and at three months
within the patients with different level of response and an ANOVA was
performed to test if this change was different between the different
levels of response.
An
ordinal
logistic
regression
analysis
was
performed
to
investigate whether the DAS28-P score at baseline was associated with
the different levels of response to treatment at three months when the
DAS28-score at the start and other possible predictors like gender, age
and previous DMARD use were corrected for in the model.
The multivariable analyses for the second aim were performed on the
total cohort only, because the CAMERA-II subgroup was too small for
multivariate analyses. Subgroups were used as covariate in the
analyses.
All analyses were performed using SPSS 20.0 software and a pvalue of <.05 was regarded as statistically significant.
Box 1. DAS28-P Score
The more subjective domain part of the DAS28 formula / total DAS28 formula =
(0.56 x sqrt(TJC28) + 0.014 x VAS-GH) / (0.56 x sqrt(TJC28) + 0.28 x sqrt(SJC28)
+ 0.70 x ln(ESR) + 0.014 x VAS-GH)
DAS28: Disease Activity Score based on 28 joints; TJC28: tender joint count based on 28
joints; VAS-GH: visual analogue scale general well-being (range 1-100); SJC28: swollen
joint count based on 28 joints; ESR: erythrocyte sedimentation rate (range ~0-140).
94
DAS28-P AND THE RESPONSE TO BIOLOGICAL TREATMENT
Table 1. Baseline characteristics
Characteristics
Age, years
Female gender (%)
Total
BiOCURA
CAMERA-II
p
52.0 (12.4)
53.0 (11.9)
50.5 (13.4)
.09
128 (74)
93 (77)
35(69)
.26
102 (67)*
71 (66)*
31 (69)*
.71
DAS28 START
4.11 (1.37)
4.32 (1.18)
3.61 (1.65)
.01
TJC 28
4.5 (2-11)^
5 (2 -11.5)^
3 (0 - 9)^
.02Δ
46.78 (26.73) 54.01 (23.87) 29.55 (25.41)
<.001
RF + status (%)
VAS GH
2 (0-4)^
2 (0-4)^
2 (0 - 5)^
.11Δ
16.5 (7-30.75)^
18 (9-31.5)^
11 (5 - 30)^
.24Δ
0.44 (0.19)
0.48 (0.18)
0.34 (0.20)
<.001
1st Interquartile, n (%)
43 (25)
21 (17)
22 (43)
<.001
2nd Interquartile, n (%)
43 (25)
31 (26)
12 (24)
.85
3rd Interquartile, n (%)
43 (25)
32 (26)
11 (22)
.57
4rth Interquartile, n (%)
43 (25)
37 (31)
6 (12)
.01
Nr of prior synthetic DMARDs
2.48 (1.21)
2.99 (1.05)
1.27 (0.45)
<.001
Smoking (%)
46 (26.7)**
28 (23.1)
18 (38.3)**
.048
SJC 28
ESR
DAS28-P score ¤
Total cohort; n = 172, BiOCURA; n = 121, CAMERA-II; n = 51.Values are mean (sd) for
continuous variables and number of patients (%) for all categorical variables unless stated
otherwise. ^Median (IQR), * 102 of 153, 71 of 108 and 31 of 45 with reported RF status,
** 46 of 168 and 18 of 47 (n = 4 no reported data), Δ Mann-Whitney U. p-value states if
there is a significant difference between the two subgroups. ¤ Fisher’s exact test regarding
the overall difference in interquartile distribution between the two subgroups: p-value .03
RESULTS
The baseline characteristics for the total cohort and both subgroups are
reported in Table 1. The DAS28 score, the subjective components of the
DAS28 (TJC28 and VAS-GH), the DAS28-P score, the number of prior
DMARDs and the number of smokers were not equally distributed over
the two cohorts, showing lower disease activity, a smaller DAS28-P
score and a lower number of prior synthetic DMARDs and smokers in the
CAMERA-II trial (not surprisingly this being an early RA cohort).
To address the primary aim, Table 2 shows the DAS28-P score
for all patients, each subgroup, and per EULAR response group, both at
baseline and after 3 months of treatment with a first biological. The
overall subjective contribution to the DAS28 was 44%, 48% and 34%
respectively at the start in the total cohort and the separate BiOCURA
95
CHAPTER 6
and CAMERA-II subgroups.
At the start, the DAS28-P score did not
differ between the response groups in the total and BiOCURA subgroups
(all between 40-49%). Only the non-responders in the CAMERA-II
sample had a lower subjective contribution and differed significantly
from the other response groups in that subgroup; DAS28-P scores were
0.42, 0.44 and 0.24 for the Good, Moderate and Non responders
respectively, (F = 6.65, p = .003). Overall, a significant change in the
DAS28-P score was observed over time in both the Total (p < .001) and
the separate BiOCURA cohort and CAMERA-II subgroups (p < .001 and p
= 0.004 respectively), showing a smaller subjective contribution. This
can be interpreted as more pronounced improvement in the subjective
parts of the DAS28. Interestingly this significant reduction of the
DAS28-P score was only observed in the Good responders (p < .001) in
the total cohort as well as the subgroups.
Table 2. The DAS28-P score and its change over time
Cohort
EULAR response
Total
All
BiOCURA
CAMERA-II*
n
Baseline
3 mnth
p
172
0.44 (0.19)
0.35 (0.24)
<.001
Good
65
0.46 (0.12)
0.26 (0.24)
<.001
Moderate
41
0.46 (0.12)
0.42 (0.20)
.16
Non
66
0.40 (0.26)
0.39 (0.23)
.66
121
0.48 (0.18)
0.38 (0.24)
<.001
Good
50
0.47 (0.12)
0.28 (0.25)
<.001
Moderate
29
0.47 (0.17)
0.44 (0.21)
.40
Non
42
0.49 (0.24)
0.47 (0.20)
.36
All
51
0.34 (0.20)
0.27 (0.21)
.004
Good
15
0.42 (0.11)
0.19 (0.13)
<.001
Moderate
12
0.44 (0.18)
0.39 (0.19)
.09
Non
24
0.24 (0.21)
0.26 (0.23)
.57
All
*Start contribution score not equally distributed in CAMERA-II: ANOVA p-value .003. The
reported p-value represents the level of significance of the performed paired t-tests.
Regarding the second aim, Table 3 shows that the DAS28-P score
at baseline was not associated with the different levels of response to
treatment at three months. The model did show that lower age, a higher
96
DAS28-P AND THE RESPONSE TO BIOLOGICAL TREATMENT
baseline DAS28 score, a lower number of prior synthetic DMARDs used,
being in the BiOCURA cohort subgroup and being male resulted in an
increase in odds of being in a higher level of response. When the
regression analysis was performed without the variable DAS28 at
baseline, the DAS-28-P score was not significantly associated with the
level of response.
Table 3. Ordinal regression analysis predicting level of response to treatment at three
months from multiple variables
Variables
DAS28-P score at baseline x100
Δ
pOR‡
Estimate
p
1.00
0.00
.88
DAS28 at baseline
1.68
0.52
<.001
Age, years
0.97
-0.04
.02
0.63
-0.46
.02
0.34
-1.08
.04
-0.94
.03
Nr. of prior DMARDs
Subgroups
CAMERA-II
BiOCURA
0
Gender
Female
0.39
RF status
Positive
1.32
0.28
.43
Smoking
Yes
0.69
-0.37
.33
Ordinal logistic regression with variables obtainable at baseline. This analysis is performed
to address the odds of being in a higher EULAR response group. Good response is the
reference category. Model information: Logit; -2 Log Likelihood final vs. Intercept: p <
.001; Pseudo R-Square: Nagelkerke 0.19; Test of Parallel lines: p = .21. ‡ Proportional
odds ratio, Δ Contribution score ranges between 0 and 1 because it is a ratio; for clear
interpretation of the particular estimate, this ratio has been multiplied by 100. When the
regression analysis was performed without the variable DAS28 at baseline, the DAS-28-P
score was not significantly associated with the level of response. n = 151 due to missing
data.
DISCUSSION
The primary aim of our present study was to investigate the presumed
disproportionate contribution of the subjective components of the DAS28
score in the disease activity score in patients who do not respond well to
treatment and to see if the subjective contribution changes over time
after the start of a new treatment step in a cohort of RA patients treated
with biologicals. We hypothesised that objective, doctor-observed and
laboratory measures would have a higher contribution at baseline (i.e.
before the start of biological treatment) in responders and that these
97
CHAPTER 6
parameters would improve more significantly after the start of this
treatment.
Our findings do not support this as the subjective components
(tender joint counts) and one of the objective components (ESR)
components of the DAS28 contributed most to the clinical response. We
conclude therefore that a disproportionate subjective contribution to the
DAS28 score is not the reason for non-response. However, the share of
the subjective components of the DAS28 became smaller over time in
patients with a good response to the therapy, suggesting that in good
responders especially also the subjective components improve, whereas
none of the items of the DAS28 seem to respond in the non-responder
group. The EULAR response groups in the cohort and subgroups did not
differ much.
In general (the one exception the non-responders in the
CAMERA-II subgroup), the DAS28-P score became smaller over time.
The results suggest that biological DMARDs affect through their blocking
ability on pro-inflammatory cytokines both inflammation (disease) and
subjective components of the diseases (illness or sickness response). 1719
In patients with RA, the swift effect of a blockade of TNF-α has been
described, showing a significant lowering in the subjective VAS-pain
within 24 hours.20 These data indicate a fast effect of TNF-α blockade on
the pain responses in the central nervous system even before a
measurable anti-inflammatory effect is achieved.20
Regarding our secondary aim we found that the DAS28-P score at
baseline is not associated with the different levels of response to
treatment at three months. These results make it difficult to base
treatment decisions on the subjective or objective characteristics of
disease activity scores. Recently, a new criterion for treatment response
as assessed by the DAS28 that exceeds random disease activity
variations in patients with RA has been established that may be useful in
steering individual therapy and stratifying clinical trials.21
The
present
study
has
some
limitations.
The
baseline
characteristics were not all equal between the two subgroups. This can
be explained by the difference in study design. CAMERA-II is a highly
protocolised strategy trial using an MTX-based treatment strategy, with
stringent steps to follow and only included early RA patients. The
98
DAS28-P AND THE RESPONSE TO BIOLOGICAL TREATMENT
BiOCURA cohort is an observational study were patients with varying
disease durations are enrolled. Patients in the CAMERA-II trial might be
making the step to a biological more quickly – as the next protocolised
step following MTX (plus prednisone or a placebo) –
than in the
BiOCURA cohort, where response is more based on current disease
status, inflammation, patient perception and clinical observations and
other treatment options like other synthetic DMARDs are no (longer an)
option. Another limitation of our study is that we do not possess
information
on
fibromyalgia,
stress,
depression
and
outcome
expectations which could have influenced our outcomes. New study
designs should include this type of patient information.
The DAS28-P score has not been widely used. While some studies
have used the subjective contribution of the DAS28 to study DMARD
intensification,22 its role in predicting pain10 and how this contribution is
affected by psychological factors,23 to our knowledge no studies have
focussed on the association between the subjective contribution and
response to treatment.
The counterintuitive findings of an equal contribution of the
subjective disease activity measures irrespective of response and the
even larger improvement in subjective measures of the DAS28 in good
responders might (partly) be a placebo effect, possibly related to the
use of biological DMARDs. It is also not clear if over time this effect is
the same.
For clinical practice we can conclude that pain at baseline is not a
reason not to start with biological DMARDs and that the presented data
do not support patient selection based on subjective contribution to
disease activity.
More research is needed for a better understanding and more
insight into the precise working of biological DMARDs on more subjective
patient reported outcomes so biological DMARDs can be used for
treating the individual patient optimally. It would be of great interest to
learn if in placebo-controlled biological DMARD research similar effects
of equal contribution of subjective and objective measures to disease
activity irrespective of response are found in RA patients.
99
CHAPTER 6
CONCLUSION
Our study shows that the largest part of improvement in disease activity
on average and especially in good responders can be accounted for by
the subjective contribution to the DAS28. The hypothesis that especially
the subjective – patient reported – components of the DAS28 have a
disproportionate contribution to the lack of response to biological
DMARD treatment was rejected Responders and non-responders did not
differ in the baseline subjective contribution, therefore the DAS28-P
value at baseline could not be linked to treatment response.
REFERENCES
1.
Verstappen SM, Jacobs JW, van der Veen MJ, et al. Intensive treatment with
methotrexate in early rheumatoid arthritis: aiming for remission. Computer Assisted
Management in Early Rheumatoid Arthritis (CAMERA, an open-label strategy trial).
Ann Rheum Dis 2007;66:1443-9.
2.
Elliott MJ, Maini RN, Feldmann M, et al. Treatment of rheumatoid arthritis with
chimeric monoclonal antibodies to tumor necrosis factor alpha. Arthritis Rheum
1993;36:1681-90.
3.
Scott DL. Biologics-based therapy for the treatment of rheumatoid arthritis. Clin
Pharmacol Ther 2012;91:30-43.
4.
Kievit W, Fransen J, Oerlemans AJ, et al. The efficacy of anti-TNF in rheumatoid
arthritis, a comparison between randomised controlled trials and clinical practice. Ann
Rheum Dis 2007;66:1473-8.
5.
Anderson J, Caplan L, Yazdany J, et al. Rheumatoid arthritis disease activity
measures: American College of Rheumatology recommendations for use in clinical
practice. Arthritis Care Res (Hoboken) 2012;64:640-7.
6.
Prevoo ML, van 't Hof MA, Kuper HH, et al. Modified disease activity scores that
include twenty-eight-joint counts. Development and validation in a prospective
longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum 1995;38:448.
7.
Moreland LW, O'Dell JR, Paulus HE, et al. A randomized comparative effectiveness
study of oral triple therapy versus etanercept plus methotrexate in early, aggressive
rheumatoid arthritis. Arthritis Rheum 2012;64:2824-35.
8.
Soubrier M, Puechal X, Sibilia J, et al. Evaluation of two strategies (initial
methotrexate monotherapy vs its combination with adalimumab) in management of
early active rheumatoid arthritis: data from the GUEPARD trial. Rheumatology
(Oxford) 2009;48:1429-34.
9.
Tak PP, Rigby WF, Rubbert-Roth A, et al. Inhibition of joint damage and improved
clinical outcomes with rituximab plus methotrexate in early active rheumatoid
arthritis: the IMAGE trial. Ann Rheum Dis 2011;70:39-46.
100
DAS28-P AND THE RESPONSE TO BIOLOGICAL TREATMENT
10.
McWilliams DF, Zhang W, Mansell JS, et al. Predictors of change in bodily pain in
early rheumatoid arthritis: an inception cohort study. Arthritis Care Res (Hoboken)
2012;64:1505-13.
11.
Pollard LC, Kingsley GH, Choy EH, et al. Fibromyalgic rheumatoid arthritis and
disease assessment. Rheumatology (Oxford) 2010;49:924-8.
12.
Coury F, Rossat A, Tebib A, et al. Rheumatoid arthritis and fibromyalgia: a frequent
unrelated association complicating disease management. J Rheumatol 2009;36:5862.
13.
Arnett FC, Edworthy SM, Bloch DA, et al. The American Rheumatism Association 1987
revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum
1988;31:315-24.
14.
Bakker MF, Jacobs JW, Welsing PM, et al. Low-dose prednisone inclusion in a
Methotrexate-Based, Tight Control Strategy for Early Rheumatoid Arthritis. A
Randomized Trial. Ann Intern Med 2012;156:329-39.
15.
van Gestel AM, Anderson JJ, van Riel PL, et al. ACR and EULAR improvement criteria
have comparable validity in rheumatoid arthritis trials. American College of
Rheumatology European League of Associations for Rheumatology. J Rheumatol
1999;26:705-11.
16.
van Gestel AM, Prevoo ML, van 't Hof MA, et al. Development and validation of the
European League Against Rheumatism response criteria for rheumatoid arthritis.
Comparison with the preliminary American College of Rheumatology and the World
Health Organization/International League Against Rheumatism Criteria. Arthritis
Rheum 1996;39:34-40.
17.
Yirmiya R. Endotoxin produces a depressive-like episode in rats. Brain Res
1996;711:163-74.
18.
Capuron L, Miller AH. Cytokines and psychopathology: lessons from interferon-alpha.
Biol Psychiatry 2004;56:819-24.
19.
Dantzer R. Cytokine, sickness behavior, and depression. Immunol Allergy Clin North
Am 2009;29:247-64.
20.
Hess A, Axmann R, Rech J, et al. Blockade of TNF-alpha rapidly inhibits pain
responses in the central nervous system. Proc Natl Acad Sci U S A 2011;108:3731-6.
21.
Behrens F, Tony HP, Alten R, et al. Development and validation of a new DAS28based treatment response criterion for rheumatoid arthritis. Arthritis Care Res
(Hoboken) 2013;65:1608-16.
22.
Dougados M, Nataf H, Steinberg G, et al. Relative importance of doctor-reported
outcomes vs patient-reported outcomes in DMARD intensification for rheumatoid
arthritis: the DUO study. Rheumatology (Oxford) 2013;52:391-9.
23.
Cordingley L, Prajapati R, Plant D, et al. Impact of psychological factors on subjective
disease activity assessments in patients with severe rheumatoid arthritis. Arthritis
Care Res (Hoboken) 2014;66:861-8.
101
CHAPTER 6
102
Chapter 7
The prospective association
between psychological distress
and disease activity in
rheumatoid arthritis: a
multilevel regression analysis
Authors
Cécile L. Overman
Ercolie R. Bossema
Henriët van Middendorp
Leoniek Wijngaards-de Meij
Suzanne M.M. Verstappen
Marcia Bulder
Johannes W.G. Jacobs
Johannes W.J. Bijlsma
Rinie Geenen
Published as:
Overman, C.L., Bossema, E.R., van Middendorp, H., Wijngaards-de Meij,
L., Verstappen, S.M.M., Bulder, M., Jacobs, J.W.G., Bijlsma, J.W.J., &
Geenen, R. (2012). The prospective association between psychological
distress and disease activity in rheumatoid arthritis: a multilevel
regression analysis. Annals of the Rheumatic Diseases, 71, 192-197.
103
CHAPTER 7
ABSTRACT
Background: Cross-sectional associations suggest a mutual impact of
disease activity and psychological distress in rheumatoid arthritis (RA),
but a prospective association has not been established.
Objective:
To
examine
concurrent
and
prospective
associations
between psychological distress and disease activity.
Methods: Patients with RA (N=545, disease duration ≤ 1 year, age 1883 years, 69% female, 64% rheumatoid factor positive) were monitored
for 5 years. The Thompson joint score and erythrocyte sedimentation
rate (ESR) were assessed every 6 months. Depressed mood and anxiety
were measured every 12 months. Multilevel regression analysis was
used. Rheumatoid factor positivity, age, and female sex were included
as covariates.
Results: Concurrent levels of psychological distress and disease activity
were positively associated (p ≤ .04). Prospectively, depressed mood was
associated with disease activity levels 6 months later (p ≤ .04). The
Thompson joint score was associated with psychological distress levels 6
months later (p ≤ .03) and also with an increase in depressed mood
over the subsequent 6 months (p = .02). No other significant
prospective associations were found (p ≥ .07).
Conclusion: Psychological distress and disease activity are positively
associated when measured at the same time as well as when measured
6 months apart. While some support was found for the idea that a
higher level of disease activity is a risk factor for an increase in
psychological distress, our results do not support the notion that
psychological distress is a risk factor for future exacerbation of disease
activity.
104
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
INTRODUCTION
Psychological distress, comprising depressed mood and anxiety, 1 is
common among patients with rheumatoid arthritis (RA). Depressed
mood is reported among 13-20% of patients with RA,2-6 with some
studies reporting rates even up to 42%.7-10 These percentages are about
twice as high as in the general population.11 Anxiety is also prevalent in
patients with RA, often accompanied by comorbid depression.9,12 The
proportion of patients with RA scoring above the clinical threshold for
anxiety
is
population.
two
11,13
to
four
greater9,12
times
than
in
the
general
As similar physiological stress systems are involved in
both psychological distress and inflammation, a mutual impact of
psychological distress and disease activity in RA could be possible.14
Psychological distress may affect disease activity by altering the
functioning of the immune, endocrine, and central nervous systems. 15
Psychological
stress
overactivation
of
and
the
distress
sympathetic-adrenal-medullary axis
pro-inflammatory cytokines,
these axes.
been
associated
hypothalamic-pituitary-adrenal
16-20
18
have
15,21-25
axis
with
and
and with increased levels of
possibly fuelling the activation of
The enduring activation of stress axes can cause the
immune system to downregulate its glucocorticoid receptors, thereby
becoming desensitised to the inhibitory actions of the axes’ hormonal
products.16,19,26,27 This may allow an increase in pro-inflammatory
cytokines and inflammation. Furthermore, psychological distress can
indirectly
affect
physiological
mediators
and
disease
activity
by
influencing health behaviours, such as smoking, physical exercise,
doctor visits, adherence, and sleep quality.28,29 Psychological distress is
thus expected to increase disease activity in patients with RA.
In addition to the negative effects psychological distress may
have on disease activity, disease activity may also cause or increase
psychological distress. A direct causal link between inflammatory
processes and depressed mood is suggested by research showing an
increase of depressive-like behaviour after administration of proinflammatory cytokines in animals,30-32 and of depression during
immune treatment of cancer and hepatitis in humans.33-35 It has been
suggested that this negative effect can be abolished by blocking
receptors
for
these
cytokines,36
or
by
pre-treatment
with
105
CHAPTER 7
antidepressants.32,33 RA disease activity may also indirectly contribute to
psychological
distress
due
to
pain
and
disability,10,37
and
unpredictable and sometimes uncontrollable course of the disease.
the
29,37
A
period of more severe disease activity may thus increase the level of
psychological distress in patients with RA.
Although many patients with RA attribute their disease flares to
psychological
stress,14,38
research
so
far
did
not
conclusively
demonstrate a relation between patients’ psychological status and
disease activity in prospective studies. Some studies did find a
concurrent association between depression or anxiety and objective
measures of disease activity (e.g. erythrocyte sedimentation rate
[ESR]),2,39,40 but others did not.10,41 In other patient groups or in the
general population, some studies were able to link depression or
depressed mood to higher levels of pro-inflammatory cytokines such as
interleukin-6,15,21,22,24,25,42 interleukin-1,23 and tumour necrosis factorα,24 but others did not find such an association.19,43,44 Due to these
inconsistent results and because of the cross-sectional nature of most of
the studies, the prospective link between psychological distress and
immune or disease activity remains uncertain. As yet, only one study
employed a longitudinal mixed model design to examine possible
determinants of depression and anxiety in patients with RA over a
period of 10 years.40 Depression was concurrently associated with high
disease activity and anxiety was, unexpectedly, associated with low
disease activity, which emphasizes the need to examine depressed
mood and anxiety as separate dimensions of psychological distress. This
hallmark study did not examine the prospective associations between
psychological distress and disease activity.
The aim of the current study was to examine both the concurrent
and prospective associations between psychological distress and disease
activity in patients with a recent diagnosis of RA. To achieve this goal,
our study used multilevel regression analysis to examine clinical and
psychological data of a large cohort of RA patients over a period of 5
years after diagnosis. We expected to find concurrent and also
prospective associations between psychological distress and disease
activity levels. Moreover, we hypothesized that higher than average
levels of psychological distress would be associated with a subsequent
106
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
increase in disease activity. Also, higher than average levels of disease
activity were hypothesized to be associated with a subsequent increase
in psychological distress.
METHODS
Participants
The study population comprised 545 patients with a recent diagnosis of
RA, recruited between 1990 and 2002 in six rheumatology outpatient
clinics of the Utrecht Foundation for Rheumatism Research (SRU) in the
Utrecht region, The Netherlands, who were enrolled in a prospective trial
comparing the effectiveness of several drug treatment strategies. The
study was approved by the ethical review boards of all participating
hospitals. Details of the study have been described.45 Briefly, inclusion
criteria were (1) a diagnosis of RA as defined by the revised criteria of
the American Rheumatism Association,46 (2) disease duration ≤ 1 year,
and (3) age ≥ 17. Patients diagnosed with psychiatric disorders, comorbid diseases or drug usage, possibly interfering with one of the
therapeutic strategies, and fertile female patients not taking adequate
contraceptive measures or who were breastfeeding were excluded from
the study.
Psychological and clinical assessments
Psychological distress was assessed at baseline, before randomised
treatment with one of four medication strategies, and then annually until
five years after inclusion.45 Psychological distress was measured with the
anxiety- and depressed mood-scales of the Impact of Rheumatic
diseases on General health and Lifestyle (IRGL) questionnaire.47 The
anxiety-scale consists of ten items (range 10-40) derived from the
Spielberger State-Trait Anxiety Inventory (STAI-DY).48,49 The depressed
mood-scale consists of six items (range 0-24), derived from a
questionnaire by Zwart and Spooren.50
These items of the IRGL are
scored on a 4-point Likert scale with higher scores representing more
psychological distress. Scores ≥ 6 for depressed mood and ≥ 23 for
anxiety are considered to indicate distress according to a norm group of
362 RA patients.47 Reliability and validity of the IRGL scales are
satisfactory.47
107
CHAPTER 7
Disease activity was assessed at baseline and afterwards every
three months in the first two years and once every six months in the
remaining three years. The used measures of disease activity were ESR
in mm/h (Westergren) and the Thompson articular index, a weighted
score including both swollen and painful joints (range 0-534).51
Statistical analysis
Multilevel regression analysis was applied to examine concurrent and
prospective associations between disease activity and psychological
distress variables. This method of analysis accommodates missing
values obviating the need to eliminate all data from a particular case
and takes account of both within- and between-subject variance of the
hierarchical data (i.e. repeated measures within RA patients). Data were
analysed using HLM 6.0852 and SPSS 16.0.2.53
The score distributions of both the disease activity variables and
the psychological distress variables were positively skewed. After
logarithmic transformation the score distributions of ESR and anxiety,
and their residuals, reached normality. The score distributions of the
Thompson joint score and depressed mood, both with one third of the
scores being zero, and their residuals remained positively skewed after
transformation. To examine if the score distribution of these variables
would affect the results, we performed the multilevel analyses twice,
once with the original continuous scores as dependent variables and
once with categorised scores of the Thompson joint score and depressed
mood, and compared the results. The results did not differ substantially,
allowing us to leave the Thompson joint score and depressed mood as
continuous dependent variables in the final analyses. However, it was
expected that Thompson joint scores and depressed mood scores would
indicate a dichotomous distinction between having and not having joint
problems or a depressed mood and a linear effect of the scale when
having these problems. Thus, when the Thompson joint score or
depressed mood acted as independent variables, a dichotomous variant
(0 = zero and 1 = scores exceeding zero) of these variables was added
to the model to examine both effects.
Before multilevel analyses, the time trend of the psychological
distress and disease activity variables across five years was examined.
108
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
The testing of polynomial terms revealed that for every model the best
fit was acquired with an equation specifying both a linear and quadratic
trend. Covariates were determined with correlational analysis prior to
multilevel analyses. Rheumatoid factor (RF) positivity, female sex, and
age at baseline were significantly correlated with most disease activity
and psychological distress variables and were entered as covariates in
the multilevel analyses. Type of medication used, radiographic damage
score,54 education level and marital status were not significantly
correlated with psychological distress and disease activity variables, and
were not included in multilevel analyses.
In multilevel analyses, concurrent and prospective association
models were tested for each of the four dependent variables: ESR,
Thompson joint score, depressed mood and anxiety. In the concurrent
association models, the dependent variable was predicted by time
variables, covariates and the psychological distress or disease activity
variables of interest, measured at the same time as the dependent
variable. In the prospective association models, the dependent variable
was predicted by time variables, covariates, and the distress or disease
activity variables of interest, measured six months before. Every model
was tested both with and without the previous measurement (six or
twelve months before) of the dependent variable. With this addition of
the previous measurement of the dependent variable to the model, the
other variables in the prospective association models predict a change of
the dependent variable, instead of its absolute value. The three types of
models were built up step by step: from an initial model, including only
time variables (linear and quadratic); to a second model, examining the
effects of the covariates; to a final model, including all possible
explanatory variables. The significance of the effects of included
variables was determined with the Wald test. In all statistical tests,
significance levels were set at p < .05.
RESULTS
Patient characteristics and missing data
Table 1 shows the patient characteristics. Of the 545 patients with RA,
426 (78%) completed 60 to 100% (>20) of the 34 psychological and
clinical assessments. Of the 119 patients with less than 60% of the
109
CHAPTER 7
assessments completed, 86 patients completed between 40 and 60%,
and 33 patients completed 18 to 40%. Patients who completed less than
60% did not significantly differ from the other patients with respect to
baseline scores of psychological distress and disease activity (p ≥ .14)
or patient characteristics (p ≥ .41) with the exception of a more
frequent positive RF status (68% vs. 54%, p = .004) in the group with
the least missing values.
Table 1 Baseline characteristics of the 545 patients with rheumatoid arthritis
Female sex, n (%)
377
(69)
56
(14)
Males
57
(13)
Females
56
(15)
Low
172
(32)
Middle
266
(49)
High
57
(10)
Unknown
50
( 9)
46
( 8)
Age mean (SD)
Education level, n (%)
Marital status, n (%)
Single
362
(67)
Divorced
Married or cohabiting
26
( 5)
Widowed
50
( 9)
Unknown
61
(11)
Positive
349
(64)
Negative
188
(35)
Unknown
8
( 1)
Rheumatoid factor, n (%)
Education level: ‘Low’: Primary school or lower vocational secondary education. ‘Middle’:
Intermediate general secondary education or intermediate vocational education. ‘High’:
Higher general secondary education, higher vocational education, pre-university or
university education.
Description of time trends
Both psychological distress and disease activity scores declined over the
years, with a pronounced decline in the first year and a more gradual
decline in the years thereafter (Table 2). Psychological distress was
common in our patient sample. At baseline, 45% of the depressed mood
scores and 36% of the anxiety scores reflected distress. Approximately
110
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
25% of the patients still experienced psychological distress after five
years (Table 2).
Table 2. Trends for the psychological distress and disease activity variables during the
first five years after being diagnosed with rheumatoid arthritis
Partici-
Depressed
pants
mood
n*
Baseline
Anxiety
Thompson
(range 0-24)
(range 10-40)
(range 0-534) (range 0-145)
M (SD)**,
M (SD)**,
M (SD) **
percentage†
percentage†
545
5.4 (4.8), 45% 20.7 (6.4), 36%
6 months
518
-
12 months
535
18 months
486
24 months
513
30 months
441
36 months
453
42 months
48 months
M (SD) **
146.0 (103.3)
41.1 (27.8)
73.4
(93.1)
26.0 (22.3)
3.6 (4.1), 28% 18.9 (6.2), 29%
59.6
(84.6)
25.0 (22.2)
-
52.4
(76.3)
22.6 (19.6)
3.3 (4.0), 28% 18.2 (5.6), 22%
48.5
(74.5)
22.0 (18.5)
-
44.5
(74.0)
21.1 (18.4)
3.5 (4.2), 26% 18.8 (6.4), 25%
40.3
(69.4)
20.5 (18.0)
384
-
37.7
(62.1)
20.5 (17.0)
391
3.0 (3.7), 26% 18.4 (6.1), 22%
36.7
(65.7)
19.8 (17.8)
54 months
313
-
37.8
(71.2)
19.1 (15.8)
60 months
302
3.0 (3.8), 26% 18.1 (6.0), 23%
36.9
(66.5)
20.6 (17.0)
*
-
ESR
-
n = the number of participants providing scores on each time point for one or more of
the dependent variables
** M = mean, SD = standard deviation
†
Percentage of patients scoring ≥ 6 for depressed mood and ≥ 23 for anxiety
47
Concurrent association analyses
First, we examined concurrent associations between psychological
distress and disease activity variables. The final models are shown in
Table 3 for depressed mood and anxiety and in Table 4 for the
Thompson joint score and ESR. With respect to trend effects, scores on
all dependent variables decreased across the five year interval, with
most often a significant linear (time) and quadratic (time2) trend. With
respect to the covariates, RF positivity was associated with anxiety and
ESR, female sex was associated with more severe depressed mood and
anxiety, and an older age was associated with a lower Thompson joint
score and a higher ESR. After taking into account the time trends and
covariates, higher scores on both disease activity variables were
111
CHAPTER 7
associated with more severe depressed mood and anxiety and vice
versa.
Table 3. Concurrent association analyses for psychological distress
Anxiety†
Depressed mood
B‡
(SE)
p-value
B
(SE)
p-value
Trend
Time*
-0.3134
(0.0769)
< .001
-0.0053
(0.0023)
.02
Time²
0.0211
(0.0069)
.003
0.0004
(0.0002)
.08
0.4985
(0.3027)
.10
0.0266
(0.0105)
.01
Female sex
1.3799
(0.3047)
<.001
0.0526
(0.0107)
< .001
Age (years)
0.0103
(0.0105)
.33
0.0004
(0.0003)
.23
0.6902
(0.2103)
.001
0.0127
(0.0061)
.04
0.0024
(0.0012)
.05
0.0001
(0.00003)
.001
1.3058
(0.2941)
< .001
0.0456
(0.0092)
< .001
Covariates
Rheumatoid factor
positive
Disease activity
Thompson joint score
0/1**
Thompson joint score
†
ESR
*
Time consists of 11 time points, numbered 0-10, measured at baseline and every 6
months up to 5 years
** Thompson joint score 0/1 is a dichotomous variable with 0 for zero scores and 1 for
scores exceeding zero
†
ESR (erythrocyte sedimentation rate) and anxiety are logarithmically transformed
‡
Statistics of the final models are shown
Prospective association analyses of levels
Subsequently,
prospective
(i.e.
time-lagged)
associations
between
psychological distress and disease activity variables were examined.
Previous scores on the dependent variable were not taken into account.
Therefore, these analyses reflect associations between absolute levels of
psychological distress and disease activity measured six months apart.
Four associations between disease activity and psychological distress
variables were significant. Scores exceeding zero on the depressed
mood scale were associated with a higher Thompson joint score (B =
10.7163 [SE = 4.9783], p = .03) and a higher ESR six months later (B
= 0.0353 [SE = 0.0176], p = .04). Furthermore, a higher Thompson
joint score was associated with higher levels of depressed mood (B =
0.0028 [SE = 0.0013], p = .03) and anxiety (B = 0.0001 [SE =
112
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
0.00004], p = .02) six months later. The other associations in these
analyses were not significant (p ≥ .07).
Table 4. Concurrent association analyses for disease activity
ESR†
Thompson joint score
B
‡
(SE)
p-value
B
(SE)
p-value
Trend
Time
(1.8683)
< .001
-0.0863
(0.0056)
< .001
2.0132
(0.1716)
< .001
0.0061
(0.0006)
< .001
1.7249
(4.9709)
.73
0.1432
(0.0271)
< .001
Female sex
-2.9064
(5.1704)
.57
0.0450
(0.0265)
.09
Age (years)
-0.3802
(0.1794)
.03
0.0041
(0.0009
< .001
14.4978
(4.5886)
.002
0.0275
(0.0181)
.13
(0.7296)
.20
0.0051
(0.0024)
.04
(21.0731)
.009
0.2448
(0.0759)
.002
Time²
-27.8024
Covariates
Rheumatoid factor
positive
Psychological distress
Depressed mood 0/1**
Depressed mood
Anxiety†
*
0.9313
55.1736
Time consists of 11 time points, numbered 0-10, measured at baseline and every 6
months up to 5 years
** Depressed mood 0/1 is a dichotomous variable with 0 for zero scores and 1 for scores
exceeding zero
†
ESR (erythrocyte sedimentation rate) and anxiety are logarithmically transformed
‡
Statistics of the final models are shown
Prospective association analyses of change
Finally, prospective associations between psychological distress and
disease activity variables were examined, but now the previous score of
the dependent variable was taken into account. Therefore, these
analyses examined the association between psychological distress or
disease activity variables and a change in the dependent variable during
the subsequent six months (instead of its absolute value six months
later). As was to be expected, the association between the two repeated
measurements of the dependent variable was highly significant in all
models (p < .001). One model analysing the prospective association of
change was significant: a higher Thompson joint score was associated
with an increase in depressed mood during the subsequent six months
(B = 0.0034 [SE = 0.0014], p = .02). The other associations in these
analyses were not significant (p ≥ .21).
113
CHAPTER 7
DISCUSSION
The hypothesis of this study was that psychological distress and disease
activity would be both concurrently and prospectively associated. The
results partially supported our hypotheses. Psychological distress and
disease activity were indeed concurrently associated. In addition, more
severe depressed mood (but not anxiety) was associated with higher
disease activity six months later and a higher Thompson joint score (but
not a higher ESR) was associated with more severe psychological
distress six months later. Moreover, only a higher Thompson joint score
was associated with an increase in depressed mood across six months.
The other hypothesized associations of psychological distress or disease
activity with subsequent change were not confirmed.
The prevalence of depressed mood (45%) and anxiety (36%) in
our sample at baseline was largely similar to the prevalence found in
previous studies.2,3,7-10 After five years, the scores of a quarter of our
sample still reflected depressed mood and anxiety. The high number of
patients with scores indicative of psychological distress together with the
about similar decline of disease activity and psychological distress in the
first five years after diagnosis, both suggest an effect of disease activity
on psychological distress.
In multilevel regression analyses, we first took into account the
influence of time trends and patient characteristics. Consistent with
results of previous studies,56,57 a positive RF status, female sex and an
older age were associated with several disease activity and psychological
distress variables. Our findings support the notion that in patients with
more severe depressed mood, disease activity is likely higher, not only
at the same time, but also several months later and that in patients with
more swollen and painful joints, psychological distress is likely higher at
the same time and later on. These findings, however, do not support
causal or predictive conclusions. Although a causal influence of the one
variable on the other cannot be excluded, it is possible that extraneous
variables explain the observed concurrent and prospective associations.
In
the
prospective
analyses
predicting
change,
a
higher
Thompson joint score was associated with an increase in depressed
mood during the next six months, but the other associations between
disease activity variables and a subsequent change in psychological
114
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
distress were not significant. Notably, psychological distress variables
were not associated with a change in disease activity. Therefore, our
data do not support the notion that psychological stress may cause
disease flares. Research so far did indicate some weak evidence that
past stress may have a negative effect on RA disease activity 14 and may
increase the inflammatory response in healthy people. 58 However, based
on our analyses, the popular14,38 and in physiological theory grounded15
belief that psychological distress may fuel inflammatory activity should
be modified or otherwise be confirmed in future prospective research.
A major strength of this study is that it used a longitudinal design
like only one other study.40 Our study is innovative with respect to its
prospective analyses of levels and change in psychological distress and
disease activity. However, our study also has limitations. First, we used
existing data with relatively long intervals between assessments. More
frequent monitoring, for example every three months during five years,
will increase the chance of finding disease flares and substantial mood
changes. Although costly and taxing for patients, such a design would
be feasible because regular follow-up examinations every one to three
months have been recommended recently for optimal treatment. 59
Second, while the prospective analyses of absolute levels are very liberal
in suggesting predictive associations, the prospective analyses of change
are very conservative. This predictive association between absolute
levels is found when anxiety is relatively high both during and six
months after an episode of having painful and swollen joints. Then,
although the Thompson joint score does not predict a still further
increase in anxiety, the subsequent anxiety level in patients with a high
Thompson joint score is still higher than normal. Third, because we only
included the Thompson joint score and ESR as a reflection of disease
activity our findings do not generalise to cytokine and HPA-axis
functioning.
To conclude, the results suggest a positive association between
psychological
distress
and
disease
activity in
RA
patients
when
measured at the same time and when measured six months apart.
There is some minor support that a higher level of disease activity
forecasts a further increase of psychological distress six months later.
115
CHAPTER 7
However, our results do not support the notion that psychological
distress is a risk factor for future exacerbation of disease activity.
ACKNOWLEDGEMENTS
The authors thank all participating rheumatologists and research nurses
of the Society for Rheumatology Research Utrecht (SRU) for their
contribution to this paper.
REFERENCES
1.
Matthews G. Distress. In: Fink G, ed. Encyclopedia of Stress, Vol. 1. Academic Press.,
2000:723-9.
2.
Abdel-Nasser AM, Abd El-Azim S, Taal E, et al. Depression and depressive symptoms
in rheumatoid arthritis patients: An analysis of their occurrence and determinants. Br
J Rheumatol 1998;37:391-7.
3.
Creed F. Psychological disorders in rheumatoid arthritis: A growing consensus? Ann
Rheum Dis 1990;49:808-12.
4.
Dickens C, McGowan L, Clark-Carter D, et al. Depression in rheumatoid arthritis: A
systematic review of the literature with meta-analysis. Psychosom Med 2002;64:5260.
5.
Pincus T, Griffith J, Pearce S, et al. Prevalence of self-reported depression in patients
with rheumatoid arthritis. Br J Rheumatol 1996;35:879-83.
6.
Smedstad LM, Moum T, Vaglum P, et al. The Impact of Early Rheumatoid Arthritis on
Psychological Distress: A comparison between 238 patients with RA and 116 matched
controls. Scand J Rheumatol 1996;25:377-82.
7.
Covic T, Tyson G, Spencer D, et al. Depression in rheumatoid arthritis patients:
demographic, clinical, and psychological predictors. J Psychosom Res 2006;60:46976.
8.
Frank RG, Beck NC, Parker JC, et al. Depression in rheumatoid arthritis. J Rheumatol
1988;15:920-5.
9.
Isik A, Koca SS, Ozturk A, et al. Anxiety and depression in patients with rheumatoid
arthritis. Clin Rheumatol 2007;26:872-8.
10.
Margaretten M, Yelin E, Imboden J, et al. Predictors of depression in a multiethnic
cohort of patients with rheumatoid arthritis. Arthritis Rheum 2009;61:1586-91.
11.
Wiltink J, Beutel ME, Till Y, et al. Prevalence of distress, Comorbid conditions and well
being in the general population. J Affective Disord 2011;130:429-37.
12.
Vandyke MM, Parker JC, Smarr KL, et al. Anxiety in rheumatoid arthritis. Arthritis
Rheum 2004;51:408-12.
13.
Kessler RC, Wai TC, Demler O, et al. Prevalence, severity, and comorbidity of 12month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen
Psychiatry 2005;62:617-27.
116
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
14.
Geenen R, Van Middendorp H, Bijlsma JWJ. The impact of stressors on health status
and
hypothalamic-pituitary-adrenal
axis
and
autonomic
nervous
system
responsiveness in rheumatoid arthritis. Ann NY Acad Sci 2006;1069:77-97.
15.
Kiecolt-Glaser JK, McGuire L, Robles TF, et al. Emotions, morbidity, and mortality:
New perspectives from psychoneuroimmunology. Annu Rev Psychol. 2002;53:83107.
16.
Barden
N.
Implication
of
the
hypothalamic-pituitary-adrenal
axis
in
the
physiopathology of depression. J Psychiatry Neurosci 2004; 29:185-93.
17.
Claes SJ. CRH, Stress, and Major Depression: A Psychobiological Interplay. Vitam
Horm 2004;69:117-50.
18.
Maes M, Bosmans E, Meltzer HY, et al. Interleukin-1β: A putative mediator of HPA
axis hyperactivity in major depression? Am J Psychiatry 1993;150:1189-93.
19.
Miller GE, Cohen S, Ritchey AK. Chronic psychological stress and the regulation of
pro-inflammatory cytokines: A glucocorticoid-resistance model. Health Psychol
2002;21:531-41.
20.
Pariante
CM.
Depression,
stress
and
the
adrenal
axis.
J
Neuroendocrinol
2003;15:811-2.
21.
Dentino AN, Pieper CF, Rao KMK, et al. Association of interleukin-6 and other biologic
variables with depression in older people living in the community. J Am Geriatr Soc
1999;47:6-11.
22.
Maes M. Increased plasma concentrations of interleukin-6, soluble interleukin-6,
soluble interleukin-2 and transferrin receptor in major depression. J Affect Disord
1995;34:301-9.
23.
Maes M. Increased serum interleukin-1-receptor-antagonist concentrations in major
depression. J Affect Disord 1995;36:29-36.
24.
Maes M, Song C, Lin A, et al. The effects of psychological stress on humans:
Increased production of pro-inflammatory cytokines and a Th1-like response in
stress-induced anxiety. Cytokine 1998;10:313-8.
25.
Zhou D, Kusnecov AW, Shurin MR, et al. Exposure to physical and psychological
stressors
elevates
plasma
interleukin
6:
Relationship
to
the
activation
of
hypothalamic-pituitary- adrenal axis. Endocrinology 1993;133:2523-30.
26.
Pace TWW, Hu F, Miller AH. Cytokine-effects on glucocorticoid receptor function:
Relevance to glucocorticoid resistance and the pathophysiology and treatment of
major depression. Brain Behav Immun 2007;21:9-19.
27.
Raison CL, Miller AH. When not enough is too much: The role of insufficient
glucocorticoid signaling in the pathophysiology of stress-related disorders. Am J
Psychiatry 2003;160:1554-65.
28.
Kiecolt-Glaser JK, Glaser R. Methodological issues in behavioral immunology research
with humans. Brain Behav Immun 1988;2:67-78.
29.
Geenen R, Mulligan K, Shipley M, Newman S. Psychosocial dimensions of the
rheumatic diseases. In: Bijlsma JWJ, Da Silva J, Faarvang KL, Burmeister G, Hachulla
E, Mariette X, eds. EULAR Compendium on Rheumatic Diseases. London: BMJ
Publishing Group 2009:637-50.
30.
Anisman H, Merali Z. Anhedonic and anxiogenic effects of cytokine exposure. Adv Exp
Med Biol. 1999;461:199-233.
117
CHAPTER 7
31.
Frenois F, Moreau M, O'Connor J, et al. Lipopolysaccharide induces delayed
FosB/DeltaFosB immunostaining within the mouse extended amygdala, hippocampus
and
hypothalamus,
that
parallel
the
expression
of
depressive-like
behavior.
Psychoneuroendocrinology 2007;32:516-31.
32.
Yirmiya R. Endotoxin produces a depressive-like episode in rats. Brain Res
1996;711:163-74.
33.
Capuron L, Gumnick JF, Musselman DL, et al. Neurobehavioral effects of interferon-α
in cancer patients: Phenomenology and paroxetine responsiveness of symptom
dimensions. Neuropsychopharmacology 2002;26:643-52.
34.
Capuron L, Miller AH. Cytokines and psychopathology: Lessons from interferon-α. Biol
Psychiatry 2004;56:819-24.
35.
Meyers CA. Mood and cognitive disorders in cancer patients receiving cytokine
therapy. Adv Exp Med Biol. 1999;461:75-81.
36.
Maier SF, Watkins LR. Intracerebroventricular interleukin-1 receptor antagonist
blocks the enhancement of fear conditioning and interference with escape produced
by inescapable shock. Brain Res 1995;695:279-82.
37.
Evers AWM, Kraaimaat FW, Geenen R, et al. Determinants of psychological distress
and its course in the first year after diagnosis in rheumatoid arthritis patients. J
Behav Med 1997;20:489-504.
38.
Affleck G, Pfeiffer C, Tennen H, Fifield J. Attributional processes in rheumatoid
arthritis patients. Arthritis Rheum 1987;30:927-31.
39.
Hider SL, Tanveer W, Brownfield A, et al. Depression in RA patients treated with antiTNF is common and under-recognized in the rheumatology clinic. Rheumatology
(Oxford) 2009;48:1152-4.
40.
Ødegård S, Finset A, Mowinckel P,et al. Pain and psychological health status over a
10-year period in patients with recent onset rheumatoid arthritis. Ann Rheum Dis
2007;66:1195-201.
41.
Bijlsma JWJ, Huiskes CJAE, Kraaimaat FW, et al. Relation between Patients Own
Health Assessment and Clinical and Laboratory Findings in Rheumatoid-Arthritis. J
Rheumatol 1991;18:650-3.
42.
Lutgendorf SK, Garand L, Buckwalter KC, et al. Life stress, mood disturbance, and
elevated interleukin-6 in healthy older women. J Gerontol Ser A Biol Sci Med Sci
1999;54:M434-9.
43.
Nabi H, Singh-Manoux A, Shipley M, et al. Do psychological factors affect
inflammation and incident coronary heart disease: The whitehall II study. Arterioscler
Thromb Vasc Biol 2008;28:1398-406.
44.
Steptoe A, Kunz-Ebrecht SR, Owen N. Lack of association between depressive
symptoms and markers of immune and vascular inflammation in middle-aged men
and women. Psychol Med 2003;33:667-74.
45.
Verstappen SMM, Jacobs JWG, Bijlsma JWJ, et al. Five-year followup of rheumatoid
arthritis patients after early treatment with disease-modifying antirheumatic drugs
versus treatment according to the pyramid approach in the first year. Arthritis Rheum
2003;48:1797-807.
118
THE PROSPECTIVE ASSOCIATION BETWEEN DISTRESS AND DISEASE IN RA
46.
Arnett FC, Edworthy SM, Bloch DA, et al. The American Rheumatism Association 1987
revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum
1988;31:315-24.
47.
Huiskes CJAE, Kraaimaat FW, Bijlsma JWJ. Measuring health status in rheumatoid
arthritis: development and refinement of a Dutch health status instrument. Gedrag
en Gezondheid 1990;18:78-89.
48.
Spielberger CD, Gorsuch RL, Lushene RE. Manual of the State-Trait Anxiety
Inventory. Palo Alto, CA: Consulting Psychologists Press, 1970.
49.
Van
der
Ploeg
HM,
Defares
PB,
Spielberger
CD.
Handleiding
bij
de
ZelfBeoordelingsVragenlijst ZBV. Lisse: Swets & Zeitlinger, 1980.
50.
Zwart F, Spooren J. Ontwikkeling van een zelfbeoordelingsvragenlijst voor depressie
(Development of a self-report questionnaire for depression). Utrecht: University
Medical Center Utrecht, 1982.
51.
Thompson PW, Silman AJ, Kirwan JR, et al. Articular indices of joint inflammation in
rheumatoid arthritis. Correlation with the acute-phase response. Arthritis Rheum
1987;30:618-23.
52.
Raudenbush SW, Bryk AS, Cheong YF, et al. HLM 6: Hierarchical Linear and Nonlinear
Modeling. Lincolnwood, IL: Scientific Software International, 2004.
53.
SPSS 16.0 for Windows. version 16.0.2, Chicago IL: SPSS Inc, 2008.
54.
Van Der Heijde D. How to read radiographs according to the Sharp/van der Heijde
method. J Rheumatol 2000;27:261-3.
55.
Hox J. Multilevel Analysis: techniques and applications. Mahwah (NJ): Lawrence
Erlbaum Associates, 2002.
56.
Dowdy SW, Dwyer KA, Smith CA, et al. Gender and psychological well-being of
persons with rheumatoid arthritis. Arthritis Care Res 1996;9:449-56.
57.
Radovits BJ, Fransen J, Van Riel PLCM, et al. Influence of age and gender on the 28joint Disease Activity Score (DAS28) in rheumatoid arthritis. Ann Rheum Dis
2008;67:1127-31.
58.
Miller GE, Rohleder N, Cole SW. Chronic interpersonal stress predicts activation of
pro- and anti-inflammatory signaling pathways 6 months later. Psychosom Med
2009;71:57-62.
59.
Smolen JS, Aletaha D, Bijlsma JWJ, et al. Treating rheumatoid arthritis to target:
Recommendations of an international task force. Ann Rheum Dis 2010;69:631-7.
119
CHAPTER 7
120
Chapter 8
General discussion
121
CHAPTER 8
GENERAL DISCUSSION
This thesis examined the burden of fatigue, physical disability, and
psychological distress in association and interaction with inflammatory
disease activity and deviant hormonal levels in patients with a rheumatic
disease. The six studies yielded the following main conclusions:
 Severe fatigue, comparable to a level of fatigue in chronic fatigue
syndrome, is widespread in rheumatic diseases. In 30 rheumatic
diseases, the prevalence of severe fatigue ranges from 35% to 82%.
Overall, one in two patients is severely fatigued (chapter 2).
 Low
dehydroepiandrosterone
associated
with
high
sulphate
fatigue
in
(DHEAS)
patients
with
levels
are
systemic
not
lupus
erythematosus (SLE; chapter 3).
 Fatigue in patients with rheumatoid arthritis (RA) is unrelated to
inflammatory disease activity. Neither a patient’s overall level of
fatigue and disease activity nor within-patient change in fatigue and
disease activity are associated (chapter 4).
 Among patients with a recent RA diagnosis, the number of patients
with
good
physical
function
and
psychological
well-being
has
increased considerably over the last two decades. Among other
changes, the reduction in disease activity is indicated to have
contributed to this improvement (chapter 5).
 In patients with RA, a lack of response to treatment with biologicals is
not attributable to high scores on the subjective, patient-reported
components of the Disease Activity Score based on 28 joints
(DAS28). The subjective burden of disease activity was found to
improve
during
treatment
with
biologicals,
especially
in
good
responders (chapter 6).
 In patients with RA, a high level of psychological distress is
associated with a high level of disease activity. While a high level of
disease activity may cause psychological distress to increase, the
popular notion that psychological distress can worsen disease activity
is not supported by our research (chapter 7).
122
GENERAL DISCUSSION
FATIGUE
Fatigue is generally considered a huge problem in rheumatic disease.1-4
Nevertheless, little research is devoted to this debilitating symptom. As
an illustration, in the past 10 years, of the 11,253 articles with
rheumatoid arthritis in the title, only 84 titles (0.7%) also include the
word fatigue. Moreover, hardly anything is known about the pathological
substrate of fatigue. It was a starting-point in this thesis that fatigue
should be looked at from a biopsychological perspective, particularly
when examining fatigue in chronic inflammatory diseases. It is obvious
that only part of the multiple factors that affect the initiation and
persistence of fatigue could be investigated, but any contribution in this
field is welcomed very much by patients and professionals that consider
fatigue a core problem.1,5 Three main problems relating to fatigue in
rheumatic diseases were studied in this thesis: its prevalence, a possible
physiological parameter that might play a role, and inflammation as
related to stable individual differences and within-subject changes in
fatigue.
A thorough study of the prevalence of fatigue in rheumatic
diseases would demand research in a fully random sample of patients in
the population, the certification of rheumatic diseases by a medical
specialist, a large sample, and preferably also the identification of
fatigue according to classification criteria over and above self-report. So
far, not one study has met all these demands of a thorough prevalence
study and our study, described in chapter 2, does have shortcomings.
However, there were strengths as well. The study focused on severe
fatigue using a stringent cut-off criterion indicating a level of fatigue
comparable to the level of fatigue in chronic fatigue syndrome, and it
used this uniform measure to assess the occurrence of severe fatigue
across 30 rheumatic diseases in a worldwide sample. With the
prevalence of severe fatigue ranging from 35% in patients with
osteoarthritis to 82% in patients with fibromyalgia and a prevalence of
around 50% in single inflammatory rheumatic diseases, this study
clearly shows that severe fatigue is a widespread problem in all
rheumatic diseases. The results of our study indicating that – on
average – one in two patients with a rheumatic disease is severely
fatigued and results of other studies showing the detrimental effects of
123
CHAPTER 8
fatigue for patients, the near environment, and society at large, 1,6
emphasize that a better understanding of fatigue is crucial.
Research into fatigue is hampered by the complexity of this
symptom. Fatigue is an experience with both physical and psychological
aspects in which neurological, endocrine as well as psychological
processes may play a role.7,8 Possibly, various processes can induce the
state of alarm called fatigue which motivates a person to rest aimed at
psychophysiological recovery. Since fatigue is multifactorial, it is unlikely
that one factor by itself controls fatigue. Still, both theory and previous
empirical results hinted to the possible vitalizing role of the hormone
DHEA and its sulphate ester DHEAS.9 However, contrary to what we
expected, patients with SLE with low DHEA(S) levels reported similar or
even less fatigue than patients with SLE with normal DHEA(S) levels
(chapter 3). Although this result does not rule out that the endocrine
system including DHEA(S) may play a role in fatigue, the alleged
vitalizing promise of DHEA(S) in this group was certainly not indicated.
Perhaps an abnormal DHEA(S):cortisol ratio that has been shown in
non-inflammatory disorders10-14 might reflect fatigue or might even play
a role in the persistence of fatigue. However, it is also conceivable that
the low DHEA(S) levels that are found in multiple rheumatic diseases9,1518
are more a marker of chronic inflammation than of fatigue. A
randomized controlled trial in our group of patients with SLE showed
that also the administration of DHEA did not reduce fatigue.19 Apart from
in pathological conditions such as Addison’s disease,20 there are no
indications whatsoever that a single endocrine parameter is of clinical
relevance for fatigue.
Considering
the
high
prevalence
of
fatigue
in
rheumatic
diseases, it is unlikely that not some sort of physiological process
associated with inflammation contributes to the initiation or persistence
of
fatigue.
An
association
between
inflammation
and
fatigue
in
rheumatic diseases seems likely for at least three reasons: (1) Many
patients with a rheumatic disease as well as doctors regard fatigue as a
reflection of underlying inflammatory activity.1,21-23 (2) Animal research
and studies in patients undergoing immunotherapy showed that fatigue
may be induced by increased levels of pro-inflammatory cytokines that
also play a key role in rheumatic inflammation.24-29 (3) When inhibition
124
GENERAL DISCUSSION
of pro-inflammatory cytokines with biologicals was first introduced as a
treatment of RA, it was indicated in clinical practice30 and shown by
randomized trials31,32 that patients experienced a meaningful reduction
in fatigue. However, the importance of inflammatory processes in
inducing
and
maintaining
fatigue
in
rheumatic
diseases
is
also
questioned by research that repeatedly showed no or only small
associations between levels of inflammatory activity and fatigue.33-43 We
argued that an association could perhaps not have been found because
these studies focused on the association between individual differences
in the level of inflammatory activity and fatigue, thereby concealing an
association between the fluctuations in inflammation and fatigue over
time. Our study in chapter 4 showed that - as expected - individual
differences in the level of inflammatory activity and the level of fatigue
were not associated, but - unexpectedly - intra-individual changes in
inflammatory activity and fatigue were not associated either. Thus, even
the core pathological feature of rheumatic disease, inflammation, does
not seem to be related to fatigue; our study adds to the existing
evidence
that
inflammation
and
fatigue
are
mostly
independent
processes.
Everything considered, research into the biological basis of
fatigue in rheumatic diseases has yielded little result so far. Both our
study, described in chapter 4, and previous research showed individual
differences in fatigue levels in rheumatic diseases are rather stable over
time.22,44 To prevent fatigue from becoming chronic, it appears of
utmost importance to know when, why and in whom these individual
differences in the level of fatigue come about.
First, fatigue may already arise in the early stages of rheumatic
disease. If this is the case, then the early stages of rheumatic disease
might provide a window of opportunity for preventing chronic fatigue.
Behavioural interventions such as life-style education, physical exercise
and sleep hygiene training, and cognitive behavioural therapy (CBT)
which have been indicated to ameliorate chronic fatigue,8,45-47 could
perhaps also be used to prevent acute fatigue from becoming chronic by
improving self-management, by targeting risk factors such as sleep
disturbance and obesity, and by motivating patients to engage in
physical exercise and valued activities.
125
CHAPTER 8
Second, factors involved in the initiation of fatigue may be others
than those involved in maintaining fatigue. The level of fatigue might be
set by inflammation in the early stages of rheumatic disease and then
maintained by behavioural factors. Research showed that already a first
disease flare-up and the associated increase in pro-inflammatory
cytokines27,48,49 may result in fatigue as well as neurochemical changes
in the brain. These neurochemical changes may maintain and enhance
fatigue by reducing behavioural motivation and flexibility and inducing
uncertainty about the usefulness of ones actions, which may disturb
habit formation, turning simple everyday activities into an effort, and
reduce
engagement
in
physical
activity.50
Besides
behavioural
interventions to prevent or improve chronic fatigue, pharmacological
interventions, which are an obvious intervention for acute inflammation,
might potentially also modify the neurochemical changes that underlie
fatigue.
Third,
research
shows
that
female
patients,
patients
who
experience more pain and physical disability, patients with little social
support, and patients who experience or have experienced psychological
distress may have an increased risk for developing chronic fatigue.22,44,51
But contradictory results have also been reported51 and a genetic
component has hardly been investigated.52
Our study showed that fatigue is a prevalent problem in
rheumatic diseases and that inflammation and fatigue are rather
independent factors. A better understanding of the factors that trigger
and maintain fatigue is essential. In rheumatology, unravelling the
underlying mechanisms of fatigue and developing optimal treatments
should be top priorities in research and clinical practice.
PHYSICAL AND PSYCHOLOGICAL FUNCTIONING
Having a rheumatic disease imposes a considerable threat to one’s
physical functioning and psychological well-being, for example by
causing pain and tissue damage.53,54 Impaired physical functioning and
psychological distress, in turn, can negatively affect the disease process,
for example by reducing the likelihood of attending a physician when
necessary and adhering to treatment.55 Using a biopsychological
perspective, this thesis examined the interplay between disease activity
126
GENERAL DISCUSSION
and physical and psychological functioning in three studies. With
increasing complexity, each study examined a different aspect of this
interplay in patients with RA. The first study examined the possible
effect
of reduced disease activity on physical
and psychological
functioning; the second study examined the effect of the subjective psychological- burden of the disease on disease remission and the third
study examined the mutual influence of psychological distress and
disease activity.
Prospects of patients diagnosed with RA 20 years ago were
daunting: many patients ended up in a wheelchair. Nowadays, the
future of a newly diagnosed patient seems brighter. In a unique study,
described
in
chapter
5,
we
examined
physical
functioning
and
psychological well-being of patients with RA over the last two decades.
Our study received worldwide attention and we were able to relay the
hopeful message to patients that today, in spite of having RA, they have
a better opportunity to live a full and valued life than 20 years ago. It
was also good news for rheumatologists and health professionals
because our results indicated that we are on the right track with the
changes in treatment focus and strategy that have been gradually
implemented over the past decades.
Improved treatment, reflected by a decline in disease activity, is
a likely candidate to explain, at least in part, the improvement that we
observed in psychological well-being and physical functioning. Indeed,
our study showed that the reduction in disease activity could partly
explain the improvement. Another likely factor to explain part of the
improvement is a change in patient education. Nowadays, instead of
advising rest, patients are encouraged to be physically active, to live a
valued life, and to cultivate self-management strategies that help living
with a chronic disease.55 However, the effect of these gradual changes
on improved well-being and functioning are difficult to examine in a
cohort study.
Even though our hopeful message got an overall positive
reception, some patients with RA were critical because the results did
not apply to them; they still suffered from considerable physical
disability and psychological distress. Their critical reaction should be
heard. Undeniably, the clinical burden of RA is still substantial for many
127
CHAPTER 8
patients, especially for those in less prosperous countries, 56 for those
who do not have access to optimal care,57,58 and for those in whom new
treatments do not have the desired effect.59 For all those patients, more
insight into the biopsychological interplay that underlies their disease
burden is of utmost importance to be able to develop and implement
better treatment strategies so they may also enjoy improved functioning
and well-being.
Disappointing treatment effects may be related to individual
characteristics.
We
hypothesized
that
in
patients
in
whom
the
psychological burden of the disease is relatively high as compared to the
inflammatory burden, the effect of biologicals targeting inflammation
might be less because the wrong problem is targeted. However, this
hypothesis had to be rejected (chapter 6). Thus, although difficulty in
dealing with the psychological burden of the disease might be a reason
for adjunctive cognitive-behavioural management, our results suggest a
relatively high subjective burden is not a reason not to start biological
treatment.
The final study dealt with the mutual influence of psychological
and physiological processes (chapter 7). It has long been assumed that
psychological distress could exacerbate disease activity in patients with
RA,60,61 but our study did not support this popular assumption. In the
first prospective multilevel study of this hypothesis including multiple
repeated measurements, elevated levels of depressed mood and anxiety
did not worsen disease activity while having disease activity did predict
a small increase in depressed mood. Although we could not confirm an
impact of psychological distress on a subsequent increase in disease
activity, we did find that higher levels of psychological distress were
associated with higher levels of disease activity across a six-month
interval. This suggests that the best results of therapy might be
obtained when considering both the person and the disease.
RECOMMENDATIONS FOR FUTURE RESEARCH AND TREATMENT
This and earlier research showed that fatigue tends to be rather stable
in the later phases of rheumatic diseases. This may indicate that
research should focus more on the early stages of rheumatic disease.
Perhaps in the early phase there is a window of opportunity for future
128
GENERAL DISCUSSION
research
to
examine
possible
factors,
both
physiological
and
psychological, that play a significant role in fatigue becoming chronic.
These factors would be important targets for the development and
implementation of interventions that prevent fatigue from becoming
chronic.
In animal research and in a number of patients treated with
immunotherapy, pro-inflammatory cytokines seemed to trigger fatigue
and other malaise such as psychological distress. To examine that
indeed pro-inflammatory cytokines are able to induce fatigue and
psychological distress through a more direct route than by increasing
disease activity, blocking these cytokines, as is done in biological
treatment of several rheumatic diseases, should reduce fatigue and
psychological distress in patients in which disease activity is not
reduced. This should be examined in a randomized controlled trial in
which the improvement in fatigue and psychological distress in patients
whose disease activity is not improved is compared between patients
treated with biologicals and patients receiving placebo.
In treatment, the focus on the whole patient, not just on the
disease, but on the person’s mental, emotional, and physical well-being,
should
be
maintained,
because
despite
the
improvement
in
psychological distress and physical functioning over the last two
decades, for a significant percentage of patients the burden of the
disease is still high. Moreover, the focus on fatigue should be enhanced.
Patients have stressed that there needs to be more attention to fatigue
and the current thesis indicates that there is a huge number of patients
with a rheumatic disease in whom fatigue is severe. However,
rheumatologists and health professionals should also realize that
although rheumatic disease is a threat to the well-being of all patients,
not all these patients will need professional treatment to improve their
overall well-being. Many patients may benefit from prompt and
knowledgeable support by health professionals and from public health
education. It should be standard practice to encourage patients from the
start to enjoy physical exercise and live a valued life while pursuing
attainable goals.
129
CHAPTER 8
CONCLUSION
This thesis examined large patient samples adopting a biopsychological
perspective and using multiple methods to get insight into the complex
burden of fatigue, physical disability, and psychological distress in
rheumatic disease. It was observed that the relationship between
disease flare-ups and fatigue is far from 1-to-1. Furthermore, a high
psychological burden does not seem to worsen disease activity or
interfere with anti-inflammatory treatment and might even benefit from
it. Nevertheless, an additional therapeutic or public health focus on
physical activity, living a valued life, and self-management strategies
could be considered to lessen the psychological burden. While the mean
burden of rheumatic disease has been alleviated over the past decades,
the individual burden can still be substantial. Compared to two decades
ago, patients nowadays are less physically disabled, psychologically
distressed, and more often attain disease remission. However, especially
fatigue is still a severe burden for many patients and should be a top
priority in research and clinical practice.
REFERENCES
1.
Hewlett S, Cockshott Z, Byron M, et al. Patients’ perceptions of fatigue in rheumatoid
arthritis: overwhelming, uncontrollable, ignored. Arthritis Rheum 2005;53:697-702.
2.
Dupond
JL. Fatigue
in patients
with rheumatic
diseases. Joint Bone Spine
2011;78:156-160.
3.
Cleanthous S, Tyagi M, Isenberg DA, Newman SP. What do we know about selfreported fatigue in systemic lupus erythematosus? Lupus 2012;21:465-76.
4.
Barendregt PJ, Visser MR, Smets EM, et al. Fatigue in primary Sjögren's syndrome.
Ann Rheum Dis 1998;57:291-295.
5.
Kirwan J, Minnock P, Adebajo A, et al. Patient perspective: fatigue as a recommended
patient
centered
outcome
measure
in
rheumatoid
arthritis.
J
Rheumatol
2007;34:1174-7.
6.
McCrone P, Darbishire L, Ridsdale L, Seed P. The economic cost of chronic fatigue and
chronic fatigue syndrome in UK primary care. Psychol Med 2003;2:253-61.
7.
Swain MG. Fatigue in chronic disease. Clin Sci 2000;99:1-8.
8.
Stebbings S, Treharne GJ. Fatigue in rheumatic disease: an overview. Int J Clin
Rheumatol 2010;5:487-502.
9.
Derksen RHWM. Dehydroepiandrosterone (DHEA) and systemic lupus erythematosus.
Semin Arthritis Rheum 1998;27:335-47.
10.
Cleare AJ, O'Keane V, Miell JP. Levels of DHEA and DHEAS and responses to CRH
stimulation
and
hydrocortisone
treatment
Psychoneuroendocrinology 2004; 29:724-32.
130
in
chronic
fatigue
syndrome.
GENERAL DISCUSSION
11.
Turan T, Izgi HB, Ozsoy S, et al. The effects of galantamine hydrobromide treatment
on dehydroepiandrosterone sulfate and cortisol levels in patients with chronic fatigue
syndrome. Psychiatr Invest 2009; 6:204-10.
12.
Heuser I, Deuschle M, Luppa P, Schweiger U, Standhardt H, Weber B. Increased
diurnal plasma concentrations of dehydroepiandrosterone in depressed patients. J
Clin Endocrinol Metab 1998; 83:3130-3.
13.
Takebayashi M, Kagaya A, Uchitomi Y, et al. Plasma dehydroepiandrosterone sulfate
in unipolar major depression. J Neural Transm 1998; 105:537-42.
14.
Sonnenschein M, Mommersteeg PMC, Houtveen JH, Sorbi MJ, Schaufeli WB, van
Doornen LJP. Exhaustion and endocrine functioning in clinical burnout: An in-depth
study using the experience sampling method. Biol Psychol 2007; 75:176-84.
15.
Hedman M, Nilsson E, De la Torre B. Low sulpho-conjugated steroid hormone levels
in systemic lupus erythematosus (SLE). Clin Exp Rheumatol 1989; 7:583-8.
16.
Lahita RG, Bradlow HL, Ginzler E. Low plasma androgens in women with systemic
lupus erythematosus. Arthritis Rheum 1987; 30:241-8.
17.
Hartkamp A, Geenen R, Godaert GLR, et al. Effect of dehydroepiandrosterone
administration on fatigue, well-being, and functioning in women with primary Sjögren
syndrome: A randomised controlled trial. Ann Rheum Dis 2008; 67:91-7.
18.
Cutolo M, Capellino S, Sulli A, et al. Estrogens and autoinmune diseases. Ann N Y
Acad Sci 2006;1089:538-47
19.
Hartkamp A, Geenen R, Godaert GLR, Bijl M, Bijlsma JWJ, Derksen RHWM. Effects of
dehydroepiandrosterone on fatigue and well-being in women with quiescent systemic
lupus erythematosus: A randomised controlled trial. Ann Rheum Dis 2010; 69: 11441147.
20.
Hunt PJ, Gurnell EM, Huppert FA, et al. Improvement in mood and fatigue after
dehydroepiandrosterone replacement in Addison's disease in a randomized, double
blind trial. J Clin Endocrinol Metab 2000; 85:4650-6.
21.
Crosby LJ. Factors which contribute to fatigue associated with rheumatoid arthritis. J
Adv Nurs 1991;16:974-81.
22.
Repping-Wuts JWJ, Fransen J, van Achterberg T, Bleijenberg G, van Riel P. Persistent
severe fatigue in patients with Rheumatoid Arthritis. J Clin Nurs 2007;16:377-83.
23.
Rasker JJ. The enigma of fatigue. J Rheumatol 2009;36:2630-2.
24.
Anisman H, Merali Z. Anhedonic and anxiogenic effects of cytokine exposure. Adv Exp
Med Biol. 1999;461:199-233.
25.
Frenois F, Moreau M, O’Conner J, et al. Lipopolysaccharide induces delayed
FosB/DeltaFosB immunostaining within mouse extented amygdala, hippocampus and
hypothalamus
that
parallel
the
expression
of
depressive-like
behavior.
Psychoneuroendocrinology 2007;32:516-31.
26.
Yirmiya R. Endotoxin produces a depressive-like episode in rats. Brain Res
1996;711:163-74.
27.
Capuron L, Gumnick JF, Musselman DL, et al. Neurobehavioral effects of interferon-α
in cancer patients: Phenomenology and paroxetine responsiveness of symptom
dimensions. Neuropsychopharmacology 2002;26:643-52.
28.
Capuron L, Miller AH. Cytokines and psychopathology: Lessons from interferon-α. Biol
Psychiatry 2004;56:819-24.
131
CHAPTER 8
29.
Meyers CA. Mood and cognitive disorders in cancer patients receiving cytokine
therapy. Adv Exp Med Biol. 1999;461:75-81.
30.
Nikolaus S, van de Laar MAFJ. Measuring fatigue in rheumatoid arthritis. Nat Rev
Rheumatol 2011;7:562-4.
31.
De Ridder D, Geenen R, Kuijer R, Van Middendorp H. Psychological adjustment to
chronic disease. Lancet 2008;372:246–55.
32.
Chauffier K, Salliot C, Berenbaum F, Sellam J. Effect of biotherapies on fatigue in
rheumatoid arthritis: a systematic review of the literature and meta-analysis.
Rheumatology (Oxford) 2012;51:60-8.
33.
Wolfe F, Hawley DJ, Wilson K. The prevalence and meaning of fatigue in rheumatic
disease. J Rheumatol 1996;23:1407-1417.
34.
Pollard LC, Choy EH, Gonzalez J, Khoshaba B, Scott DL. Fatigue in rheumatoid
arthritis reflects pain, not disease activity. Rheumatology (Oxford) 2006;45:885-9.
35.
Bergman MJ, Shahouri SS, Shaver TS, et al Is fatigue an inflammatory variable in
rheumatoid arthritis (RA)? Analyses of fatigue in RA, osteoarthritis, and fibromyalgia.
J Rheumatol 2009;36:2788-94.
36.
Van Hoogmoed D, Fransen J, Bleijenberg G, van Riel P. Physical and psychosocial
correlates of severe fatigue in rheumatoid arthritis. Rheumatology 2010;49:1294–
1302.
37.
Stebbings S, Herbison P, Doyle TC, Treharne GJ, Highton J. A comparison of fatigue
correlates in rheumatoid arthritis and osteoarthritis: disparity in associations with
disability, anxiety and sleep disturbance. Rheumatology (Oxford) 2010;49:361–7.
38.
Campbell RCJ, Batley M, Hammond A, Fowiza I, Kingsley G, Scott DL. The impact of
disease activity, pain, disability and treatments on fatigue in established rheumatoid
arthritis. Clin Rheumatol 2012;31:717-22.
39.
Minnock P, McKee G, Bresnihan B, FitzGerald O, Veale DJ. How much is fatigue
explained by standard clinical characteristics of disease activity in patients with
inflammatory arthritis? A longitudinal study. Arthritis Car Res 2014;66:1597-1603.
40.
Burgos PI, Alarcón GS, McGwin Jr. G, Crews KQ, Reveille JD, Vilá LM. Disease activity
and damage are not associated with increased levels of fatigue in systemic lupus
erythematosus patients from a multiethnic cohort: LXVII. Arthritis Rheum 2009;
61:1179-86.
41.
Wang B, Gladman DD, Urowitz MB. Fatigue in lupus is not correlated with disease
activity. J Rheumatol 1998;25:892-5.
42.
Tench CM, McCurdie I, White PD, D'Cruz DP. The prevalence and associations of
fatigue in systemic lupus erythematosus. Rheumatology 2000;39:1249-1254.
43.
Hartkamp A, Geenen R, Kruize AA, et al. Serum dehydroepiandrosterone sulphate
levels and laboratory and clinical parameters indicating expression of disease are not
associated with fatigue, well-being and functioning in patients with primary Sjögren’s
syndrome. Clin Exp Rheumatol. 2011;29:318-321.
44.
Mancuso CA, Rincon M, Sayles W, Paget SA. Psychosocial variables and fatigue: a
longitudinal study comparing individuals with rheumatoid arthritis and healthy
controls. J Rheumatol 2006 ;33:1496-1502.
132
GENERAL DISCUSSION
45.
Evers AWM, Kraaimaat FW, van Riel PLCM, de Jong AJL. Tailored cognitive-behavioral
therapy in early rheumatoid arthritis for patients at risk: a randomized controlled
trial. Pain 2002;100:141-53.
46.
Davies H, Brophy S, Dennis M, Cooksey R, Irvine E, Siebert S. Patient perspectives of
managing fatigue in Ankylosing Spondylitis, and views on potential interventions: a
qualitative study. BMC Musculoskelet Disord 2013;14:163.
47.
Prins JB, Van der Meer JWM, Bleijenberg G. Chronic fatigue syndrome. Lancet
2006;367:346-355.
48.
Dantzer R. Cytokine-induced sickness behavior: where do we stand? Brain Behav
Immun 2001;15:7–24.
49.
McInnes IB, Schett G. Cytokines in the pathogenesis of rheumatoid arthritis. Nat Rev
Immunol 2007;7:429-42.
50.
Dantzer R, Heijnen CJ, Kavelaars A, Laye S, Capuron L. The neuroimmune basis of
fatigue. Trends Neurosci 2014;37:39-46.
51.
Nikolaus S, Bode C, Taal E, van de Laar MAFJ. Fatigue and factors related to fatigue
in rheumatoid arthritis: a systematic review. Arthritis Car Res 2013;65:1128-46.
52.
Landmark-Høyvik H, Reinertsen KV, Loge JH, et al. The genetics and epigenetics of
fatigue. PM R 2010;2:456-65.
53.
Dickens C, McGowan L, Clark-Carter D, et al. Depression in rheumatoid arthritis: A
systematic review of the literature with meta-analysis. Psychosom Med 2002;64:5260.
54.
Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health
Organ 2003;81:646-56.
55.
Geenen R, Finset A. Psycho-social approaches in rheumatic diseases. In: Bijlsma JWJ,
Da Siva JAP, Hachulla E, Doherty M, Cope A, Lioté F (Eds). EULAR textbook on
rheumatic diseases. London: BMJ Group 2012:139-62.
56.
Sokka T, Kautiainen H, Pincus T, et al. Disparities in rheumatoid arthritis disease
activity according to gross domestic product in 25 countries in the QUEST–RA
database. Ann Rheum Dis 2009;68:1666–1672.
57.
Braveman P, Gruskin S. Poverty, equity, human rights and health. Bull World Health
Organ 2003;81:539-45.
58.
Obrist B, Iteba N, Lengeler C, et al. Access to health care in contexts of livelihood
insecurity: a framework for analysis and action. Plos Med 2007;4:e308.
59.
Olsen
NJ,
Stein
CM.
New
drugs
for
rheumatoid
arthritis.
N
Engl
J
Med
2004;350:2167-79.
60.
Geenen R, Van Middendorp H, Bijlsma JWJ. The impact of stressors on health status
and
hypothalamic-pituitary-adrenal
axis
and
autonomic
nervous
system
responsiveness in rheumatoid arthritis. Ann NY Acad Sci 2006;1069:77-97.
61.
Affleck G, Pfeiffer C, Tennen H, Fifield J. Attributional processes in rheumatoid
arthritis patients. Arthritis Rheum 1987;30:927-31.
133
CHAPTER 8
134
Samenvatting
Dutch summary
135
DUTCH SUMMARY
INLEIDING
Reuma
is
een
verzamelnaam
voor
meer
dan
100
reumatische
aandoeningen die over het algemeen gepaard gaan met ontsteking,
beschadiging, pijn en stijfheid van gewrichten, spieren, pezen en
bindweefsel. Reumatoïde artritis, artrose en fibromyalgie zijn de meest
bekende vormen van reuma. Afhankelijk van de ernst, kan reuma een
grote invloed hebben op het leven van patiënten, hun directe omgeving
en de maatschappij als geheel. Patiënten worden dagelijks gehinderd in
hun functioneren door pijn, stijfheid en vermoeidheid en zijn in
vergelijking met de rest van de bevolking vaker depressief en
gespannen.
Iemands
gezondheid
wordt
bepaald
door
een
complexe
wisselwerking tussen lichamelijke en psychische processen. Het ligt voor
de hand om te denken dat de vermoeidheid en ook de depressieve
stemming en gespannenheid bij patiënten met reuma een gevolg zijn
van
de
ziekte.
Het
is
echter
nog
niet
duidelijk
bewezen
hoe
ziekteactiviteit van invloed zou kunnen zijn op vermoeidheid en
psychisch functioneren. Ook het idee dat psychische problemen de
ziekte kunnen verergeren is niet wetenschappelijk bewezen. Door
patiënten gedurende langere tijd te volgen wordt het mogelijk om
oorzakelijke verbanden tussen lichamelijke en psychische processen te
ontdekken. Daarbij is het belangrijk om te letten op verschillen tussen
patiënten
en
op
verschillen
(veranderingen)
binnen
patiënten.
Verschillen tussen en binnen patiënten worden immers door andere
processen bepaald.
In
dit
proefschrift
wordt
bij
mensen
met
een
reumatische
aandoening onderzocht hoe vaak ernstige vermoeidheid en verminderd
psychisch
en
fysiek
functioneren
voorkomen
en
of
en
hoe
de
wisselwerking is tussen vermoeidheid en functioneren enerzijds en
ontstekingsactiviteit, pijn en hormoon-niveaus anderzijds.
VERMOEIDHEID
Het is onduidelijk hoe vaak ernstige vermoeidheid voorkomt bij
patiënten met reumatische aandoeningen. In hoofdstuk 2 van dit
proefschrift werd dit onderzocht voor 30 verschillende reumatische
aandoeningen bij 6120 patiënten afkomstig uit landen verspreid over de
136
SAMENVATTING
hele wereld. Hierbij werd een afkappunt voor ernstige vermoeidheid
gebruikt dat was ontleend aan onderzoek bij patiënten met het
chronisch vermoeidheidssyndroom. Ernstige vermoeidheid bleek voor te
komen
bij
41
tot
57%
van
patiënten
met
een
vorm
van
ontstekingsreuma, bij 35% van patiënten met artrose en bij 82% van
patiënten met fibromyalgie (figuur 1). De kans op ernstige vermoeidheid
was verhoogd bij patiënten met meerdere reumatische aandoeningen,
een jongere leeftijd en een lagere opleiding. De cijfers voor Nederland
waren gunstiger dan voor andere landen. Over het algemeen geven de
cijfers dus aan dat één op de twee patiënten met reuma ernstig
vermoeid is.
Figuur 1. Percentages van patiënten met ernstige vermoeidheid bij verschillende
reumatische aandoeningen. n = het totaal aantal onderzochte patiënten met die
aandoening.
Bij patiënten met reuma is in vergelijking met gezonde mensen de
hoeveelheid
van
het
in
het
bloed
voorkomende
hormoon
137
DUTCH SUMMARY
dehydroepiandrosteron (DHEA) laag. Dit hormoon heeft mogelijk een
vitaliserende werking en zou een rol kunnen spelen in de ernstige
vermoeidheid van patiënten met een reumatische aandoening. Wij
onderzochten
het
bij
DHEA
behorende
sulfaat
(DHEAS)
bij
60
vrouwelijke patiënten met systemische lupus erythematosus (hoofdstuk
3).
De patiënten waren meer vermoeid en hadden lagere waarden van
DHEAS in het bloed dan hun 60 gezonde leeftijdsgenoten. Er was echter
geen verband tussen lagere waarden van het hormoon en de ernst van
de vermoeidheid. Bij patiënten die geen prednison gebruikten was
onverwacht de vermoeidheid zelfs hoger wanneer er meer DHEAS in het
bloed zat. Dit hormoon biedt dus geen verklaring voor de vermoeidheid
bij deze reumatische ziekte. Het onderzoek was waarschijnlijk te
eenzijdig gericht op één hormoon. Om de complexiteit van vermoeidheid
te begrijpen zal een samenspel van verschillende lichamelijke factoren
en leefstijlfactoren moeten worden onderzocht.
Het lijkt logisch dat het veelvuldig voorkomen van vermoeidheid
bij
patiënten
met
reumatische
aandoeningen
op
enigerlei
wijze
samenhangt met de ziekte. Bij een ontsteking zijn bepaalde stoffen
actief: cytokines. Deze stoffen in het afweersysteem sturen een signaal
naar het brein waardoor een gevoel van vermoeidheid en malaise
ontstaat. Op grond van de werking van cytokines is te verwachten dat er
een verband gevonden wordt tussen de ernst van de ontsteking en de
mate van vermoeidheid. Dit verband is echter klein of afwezig bij
patiënten met reumatoïde artritis. Dit is opmerkelijk, omdat ook
patiënten
en
reumatologen
vermoeidheid
wel
toeschrijven
aan
onderliggende ziekteactiviteit.
We dachten dat misschien verschillen in vermoeidheid tussen
patiënten niet zouden samenhangen met ziekteactiviteit. Dit werd
inderdaad bevestigd in een onderzoek bij 248 patiënten met reumatoïde
artritis die begonnen aan een behandeling met biologicals (medicijnen
die de werking van cytokines remmen) en zes maanden gevolgd werden
(hoofdstuk 4). We verwachtten daarentegen ook dat veranderingen in
vermoeidheid
binnen
patiënten
wel
zouden
samenhangen
met
veranderingen in ziekteactiviteit. Dit verband werd echter ook niet
gevonden. Vermoeidheid lijkt in patiënten die al een tijd ziek zijn een
138
SAMENVATTING
redelijk stabiel kenmerk te zijn geworden dat geen verband meer heeft
met wisselingen in ziekteactiviteit. Dat wijst erop dat behandeling die
gericht is op het terugdringen van de ziekteactiviteit niet de aangewezen
manier is om vermoeidheid te bestrijden.
PSYCHISCH EN LICHAMELIJK FUNCTIONEREN
De afgelopen 20 jaar is de behandeling met geneesmiddelen van
reumatoïde
artritis
verbeterd.
Er
wordt
nu
eerder
gestart
met
geneesmiddelen en er zijn betere medicijnen gekomen. Ook is de
behandeling over omgaan met reuma verbeterd. Terwijl in het verleden
patiënten werd geadviseerd om rust te houden, wordt tegenwoordig
benadrukt dat patiënten er goed aan doen in beweging te blijven en een
actief en waardevol leven te blijven leiden ondanks de reuma. Wij
vroegen ons af in hoeverre deze ontwikkelingen positieve gevolgen
hebben gehad voor het welbevinden en functioneren van patiënten
(hoofdstuk 5). We onderzochten de veranderingen in welbevinden en
functioneren bij 1151 patiënten bij wie tussen 1990 en 2011 reumatoïde
artritis werd gediagnosticeerd. Patiënten in al die jaren werden gevolgd
vanaf de diagnose tot en met vier jaar na de start van behandeling.
Depressieve
stemming
en
gespannenheid
bleken
te
zijn
afgenomen. Twintig jaar geleden kwamen depressieve stemming en
gespannenheid na vier jaar behandeling nog voor bij een kwart van de
patiënten met reumatoïde artritis; vandaag de dag nog bij één op de
acht patiënten. De grootste winst was er voor fysieke beperking. Twintig
jaar geleden was de helft van de patiënten behoorlijk fysiek beperkt na
vier jaar van behandeling; op dit moment geldt dat nog voor een kwart
van de patiënten (figuur 2). Deze gunstige ontwikkeling lijkt deels te
danken te zijn aan de daling van ziekteactiviteit, maar ook een
verbeterde voorlichting zal hebben bijgedragen aan een betere kwaliteit
van leven. Al met al kunnen we stellen dat vandaag de dag minder
patiënten met reumatoïde artritis negatieve gevolgen van hun ziekte
ondervinden dan twintig jaar geleden.
139
DUTCH SUMMARY
Figuur 2. De verandering van depressieve stemming, gespannenheid en fysieke beperking
van patiënten met reumatoïde artritis tussen 1994 en 2011. Weergegeven wordt het
precieze percentage patiënten (de staven) dat na vier jaar behandeling nog depressief,
gespannen of fysiek beperkt is en de trend (lijn).
Één
van
de
gunstige,
nieuwe
behandelmogelijkheden
voor
patiënten met reumatoïde artritis is de behandeling met biologicals.
Helaas zijn er echter toch nog behoorlijk wat patiënten die geen baat
hebben bij deze behandeling. Wij onderzochten of biologicals minder
werken bij patiënten die zich erg ziek voelen en veel pijn hebben terwijl
hun ontstekingsactiviteit niet zo hoog is. Wij onderzochten dit bij 172
patiënten met reumatoïde artritis die voor het eerst behandeld werden
met een biological (hoofdstuk 6).
Tegen de verwachting in bleek dat de ervaring van malaise en pijn
bij de start van de behandeling niet voorspellend was voor het succes
van de behandeling. Bij patiënten die goed reageerden op behandeling
namen hun malaise en pijn zelfs sterker af dan hun ontstekingsactiviteit.
We kunnen dus stellen dat patiënten die veel malaise en pijn van de
ziekte ervaren evenveel baat hebben bij een behandeling met biologicals
als andere patiënten. Dit zou mede kunnen komen doordat biologicals
de werking van cytokines verminderen en deze cytokines niet alleen een
rol spelen bij ontsteking, maar ook het gevoel ziek te zijn beïnvloeden.
140
SAMENVATTING
Depressieve stemming en gespannenheid komen bij patiënten met
reumatoïde artritis ongeveer twee keer zo vaak voor als in de algemene
bevolking. Deze psychische stress en de ziekteactiviteit kunnen elkaar
mogelijk verergeren. Aan de ene kant zou psychische stress de
ziekteactiviteit kunnen verergeren door het lichaam aan te zetten tot
meer cytokineproductie en door gezond gedrag te verminderen (meer
roken, niet naar de dokter gaan, minder bewegen, medicatie niet
innemen, etc.). Aan de andere kant zou ziekteactiviteit psychische
stress kunnen verergeren doordat ontstekingen gepaard gaan met meer
cytokines en door de bijkomende pijn, stijfheid en beperking. Veel
patiënten hebben het idee dat de ernst van de ontsteking en pijn
toeneemt na een psychisch stressvolle periode. Dit idee is echter nooit
wetenschappelijk bewezen. Wij onderzochten dit bij 545 patiënten met
reumatoïde artritis die gedurende de eerste vijf jaar van behandeling
gevolgd werden (hoofdstuk 7).
Patiënten hadden wanneer ze meer depressief en gespannen
waren wel meer ontsteking en pijn dan wanneer ze minder psychische
stress ervoeren en zes maanden na een psychisch stressvolle periode
was hun ziekteactiviteit nog altijd verhoogd. Een psychisch stressvolle
periode bleek echter de ziekteactiviteit zes maanden later niet te hebben
verergerd. Wel bleek een periode van verhoogde ziekteactiviteit de
stemming van patiënten gemiddeld licht te kunnen verslechteren; de
gespannenheid van patiënten nam er echter niet door toe. Onze
resultaten ondersteunen het onder patiënten met reumatoïde artritis
veel voorkomende idee dat psychische stress ziekteactiviteit kan doen
oplaaien dus niet.
BELANGRIJKSTE CONCLUSIES
 Bij
patiënten
met
reuma
is
ernstige
vermoeidheid
een
veel
voorkomend probleem.
 Lage
bloedwaarden
van
het
hormoon
DHEA(S)
kunnen
de
vermoeidheid bij systemische lupus erythematosus niet verklaren.
 Verhoogde ziekteactiviteit kan de vermoeidheid bij reumatoïde artritis
niet verklaren.
141
DUTCH SUMMARY
 Patiënten met reumatoïde artritis zijn tegenwoordig minder depressief,
gespannen en fysiek beperkt dan twintig jaar geleden. Een daling van
de ziekteactiviteit lijkt hier deels verantwoordelijk voor te zijn.
 Bij patiënten met reumatoïde artritis lijken psychische malaise en pijn
het behandelsucces van ontstekingsremmers niet in de weg te staan.
 Bij patiënten met reumatoïde artritis lijken depressieve stemming en
gespannenheid hun ziekteactiviteit niet te verergeren.
142
Dankwoord
Acknowledgements
143
ACKNOWLEDGEMENTS
Het is zover. Het laatste woord is geschreven, de laatste komma en punt
zijn gezet; mijn proefschrift is af, mijn tijd als promovenda voorbij. Nu
ik terugblik op die tijd en de berg werk die is verzet zijn er mensen die
ik wil bedanken, omdat zij het werk lichter hebben gemaakt en mijn tijd
als promovenda bijzonder.
Mijn dank gaat ten eerste uit naar Rinie, zonder wie dit proefschrift niet
geschreven had kunnen worden. Ik ken niemand die enthousiaster is
over zijn werk of daaraan meer is toegewijd. Hierdoor kon ik praktisch
altijd (zeven dagen per week, dag en nacht) bij jou terecht met vragen
over mijn onderzoek en artikelen en altijd rekenen op een snelle, maar
ook uitgebreide feedback met oog voor detail. Jouw enthousiasme en
grote vertrouwen in mij hebben mij gemotiveerd om te blijven
doorgaan, net een tandje verder te willen gaan en daarmee mijn
perfectionisme verder te perfectioneren.
Ercolie, jou wil ik bedanken voor je supervisie en gezelligheid. Ik ben blij
dat ik met jou heb mogen samenwerken en ik vond het gezellig dat we
een kamer deelden bij het congres in Athene. Met jouw eigen
perfectionisme,
maar
ook
kordaatheid,
snelheid,
vrolijkheid
en
hartelijkheid zorgde jij voor een prettige, constructieve samenwerking
waarbinnen onze gezamenlijke artikelen nog beter werden terwijl je mij
vertrouwen gaf in mijn eigen kunnen.
Hans Bijlsma wil ik bedanken voor zijn aansturing op afstand via
hartelijk, bondig en helder commentaar op onderzoek en manuscripten.
Mijn dank gaat ook uit naar alle collega’s die als coauteur hebben
bijgedragen aan de artikelen in dit proefschrift. Maud wil ik daarbij
speciaal bedanken. Wij hebben compleet verschillende werkstijlen, maar
die bleken elkaar wel goed aan te vullen en hebben geleid tot twee
mooie artikelen. Naast dat onze samenwerking productief was, was deze
ook gezellig; ons overleg vond meestal plaats tussen de gesprekken
tijdens lunch of koffie door. Ook ben ik dankbaar dat je me als een
vriendin steunde toen ik dat nodig had en daarvoor tijd maakte terwijl je
zelf omkwam in het werk.
144
DANKWOORD
Het toch over het algemeen solitair werken aan mijn onderzoek werd
gelukkig ook regelmatig onderbroken door overleg, congressen, borrels,
feesten en uitjes met mijn collega’s. Ik wil daarbij David bedanken voor
zijn vriendschap. Jij hebt mijn begintijd als aio specialer gemaakt en
mijn laatste congresbezoek aan Madrid gezelliger. Tamara, Ninke en
Michelle, als mijn kamergenoten wil ik jullie bedanken voor het
verzekeren van een gezellige werksfeer met leuke gesprekken wanneer
ik op de universiteit werkte. De nog niet genoemde collega’s van de
onderzoeksgroep
Psychoreumatologie
wil
ik
bedanken
voor
de
samenwerking en ook, samen met de collega’s van KGP en collega’s die
ik bij congressen heb leren kennen, voor de gezelligheid, vriendelijkheid
en gesprekken. A special thanks to Isabel, Fer and Raquel; it was nice to
get to know you during your time in Utrecht. I hope we will stay in
contact and meet again in the near future.
Ook
wil
ik
de
patiëntvertegenwoordigers
van
ons
patiëntpanel
Psychoreumatologie hartelijk bedanken voor ons constructieve en fijne
overleg en het meedenken over en aanmoedigen van het onderzoek van
onze groep. Jullie gaven een gezicht aan de vele patiënten aan wie ik
ook dank verschuldigd ben, omdat zij de moeite namen om al de
vragenlijsten en dagboeken in te vullen die nodig waren voor mijn
onderzoek.
Nog een bedankje voor de datahulptroepen: Leoniek en Rens wil ik
bedanken voor hun hulp bij de complexe statistiek, al de researchverpleegkundigen van het UMC voor hun inzet bij de dataverzameling,
Marieke Vianen voor haar vlotte hulp en uitleg bij het verkrijgen van de
data uit het UMC, Wendy en mijn masterstudenten voor de zorgvuldige
hulp bij het invoeren van al die dagboekdata.
Dan blijven mijn paranimfen en familie over. Mam en pap, een bedankje
hier valt in het niet bij alles wat jullie in mijn leven voor mij hebben
gedaan. Jullie zijn er altijd voor mij, beiden op een geheel eigen manier,
zelfs toen ons gezin tijdens mijn aio-tijd uit elkaar viel. Dank voor de
liefde, het vertrouwen en de kracht die jullie mij hebben gegeven en
blijven geven. En meer concreet bedankt voor al die tijd die jullie de
145
ACKNOWLEDGEMENTS
afgelopen jaren hebben geïnvesteerd in oppassen, zorg, verhuizingen en
klussen, zodat ik de tijd had om dit proefschrift te schrijven.
Marloes, al bijna 32 jaar zijn wij bevriend. Ik vind het heel bijzonder dat
we al zo lang als ik me kan herinneren vriendinnen zijn. Je bent één van
de liefste en leukste personen die ik ken en al zien we elkaar door de
afstand niet meer zo vaak als toen we buurmeisjes en klasgenootjes
waren, toch voelt het altijd weer volkomen vertrouwd (eigenlijk als
familie) wanneer we samen zijn. Het was voor mij niet meer dan logisch
dat jij één van mijn twee paranimfen zou zijn. Dank voor je vriendschap
en dat je mijn paranimf wilde zijn.
Tot slot Rafael, mijn Spaanse vakantieliefde die in de afgelopen
drieënhalf jaar uitgroeide tot een gezin. Samen met onze prachtige zoon
Nathan ben jij mijn nieuwe thuis naast mijn ouders. Dank voor je steun
en liefde de afgelopen jaren en natuurlijk ook bedankt dat je mijn
paranimf wilde zijn.
146
Curriculum Vitae
147
CURRICULUM VITAE
Cécile Overman was born on May 31, 1981 in
Amsterdam, The Netherlands. She enjoyed her
childhood growing up in two villages to the north of
Amsterdam while attending school in Purmerend.
After
high
Salamanca,
school,
Spain,
she
to
spent
learn
one
Spanish
year
in
and
to
submerge herself in Spanish life and culture. In
2000, back in the Netherlands, she successfully started to study
Psychology
at
the
VU
University
in
Amsterdam
obtaining
her
“propedeuse” (a propaedeutic diploma issued after the first year of
studies) Cum Laude. While being most intrigued by the relationship
between biology, psychology and behaviour, she decided to specialize in
clinical neuropsychology. She also decided she wanted to do part of her
studies in Spain and created an exchange program between the
Psychology faculties of the VU University and the University of Malaga,
Spain. She was the first to enjoy this exchange program with an
Erasmus scholarship, lived one year in Malaga and followed several
(extra) courses in clinical and social psychology. At the beginning of
2007, she concluded her studies Cum Laude. Working in a centre of
rheumatology and rehabilitation, prompted her interest in the problems
faced by patients with a rheumatic disease. This interest and her
interest in the relationship between biology, psychology and behaviour
were perfectly combined in the PhD research project which she started
in 2010 as member of the Psychorheumatology research group at
Utrecht University and which is now described in this dissertation.
Currently, she and her Spanish boyfriend, Rafael, live in Houten
together with their beautiful one-year-old son, Nathan.
148
Publications
149
PUBLICATIONS
INTERNATIONAL PEER REVIEWED PUBLICATIONS
Jurgens, M.S., Overman, C.L., Jacobs, J.W.G., Geenen, R., Cuppen,
B.V.J., Marijnissen, A.C.A., Bijlsma, J.W.J., Welsing, P.M.J., Lafeber,
F.P.J.G., Van Laar, J.M. Contribution of the subjective components of the
Disease Activity Score to the response to biological treatment in
rheumatoid arthritis. Arthritis Care and Research 10 december 2014,
Epub ahead of print.
Overman, C.L., Jurgens, M.S., Bossema, E.R., Jacobs, J.W.G., Bijlsma,
J.W.J., & Geenen, R. (2014). Change of psychological distress and
physical disability in patients with rheumatoid arthritis over the last two
decades. Arthritis Care and Research, 66, 671-678.
Overman, C.L., Hartkamp, A., Bossema, E.R., Bijl, M., Godaert, G.L.R.,
Bijlsma, J.W.J., Derksen, R.H.W.M. & Geenen, R. (2012). Fatigue in
patients
with
systemic
lupus
erythematosus:
The
role
of
dehydroepiandrosterone sulphate. Lupus, 21, 1515-1521.
Overman, C.L., Bossema, E.R., van Middendorp, H., Wijngaards-de
Meij, L., Verstappen, S.M.M., Bulder, M., Jacobs, J.W.G., Bijlsma, J.W.J.,
& Geenen, R. (2012). The prospective association between psychological
distress and disease activity in rheumatoid arthritis: a multilevel
regression analysis. Annals of the Rheumatic Diseases, 71, 192-197.
SUBMITTED MANUSCRIPTS
Overman, C.L., Kool, M.B., Da Silva, J.A.P., Geenen, R. The prevalence
of severe fatigue in rheumatic diseases: an international study.
Overman, C.L., Marijnissen, A.C.A., van Laar, J.M., Lafeber, F.P.J.G.,
Geenen, R. Fatigue and disease activity in patients with rheumatoid
arthritis: a growth curve analysis of between-subject differences and
within-subject changes.
150