Brain (2000), 123, 1677–1687
Epidemiology of multiple sclerosis in US veterans
VIII. Long-term survival after onset of multiple sclerosis
Mitchell T. Wallin,1 William F. Page2 and John F. Kurtzke1
1Neurology
Service, Veterans Affairs Medical Center and
Georgetown University Medical School, and 2Medical
Follow-up Agency, Institute of Medicine, National Academy
of Sciences, Washington, District of Columbia, USA
Correspondence to: Mitchell T. Wallin, MD, MPH,
Neurology Service, VA Medical Center, #127,
50 Irving Street, NW, Washington, DC 20422, USA
E-mail: [email protected]
Summary
Survival to 1996 was analysed for nearly 2500 veterans
of World War II who were rated as ‘service-connected’
for multiple sclerosis as of 1956 by the then Veterans
Administration. Survival from onset was defined for all
white women and black men, and a random sample of
white men. Median survival times from onset were 43
years (white females), 30 years (black males) and 34 years
(white males). Crude 50-year survival rates were 31.5%
(white females), 21.5% (black males) and 16.6% (white
males), but only the white females and white males were
significantly different. A proportional hazard analysis was
used to identify risk factors for mortality from multiple
sclerosis onset year. Significant risk factors included male
sex (risk ratio: 1.57), older age at onset (risk ratio: 1.05
per year) and high socioeconomic status (risk ratio:
1.05 per socioeconomic status category). There were no
statistically significant differences in survival following
multiple sclerosis onset by race or latitude of place of
entry into military service, both significant risk factors
associated with the development of multiple sclerosis.
Standardized mortality ratios utilizing national US data
(for 1956–96) showed a marked excess for all three race–
sex groups of multiple sclerosis cases, with little difference
among them, but with a decreasing excess over time.
Relative survival rates, used to compare the survival of
multiple sclerosis cases with that of other military
veterans, did not differ significantly by sex–race group,
nor by latitude of place of entry into military service, but
did differ significantly by socioeconomic class. The lack
of difference in male and female relative survival rates
suggests that the significant difference in survival between
male and female multiple sclerosis cases is, at least in
part, a result of sex per se and not the disease.
Keywords: multiple sclerosis; survival; veterans
Abbreviations: EAD ⫽ entry into active duty; KC ⫽ Korean Conflict; SES ⫽ socioeconomic status; SMRs ⫽ standardized
mortality ratios; VA ⫽ Department of Veterans Affairs (formerly Veterans Administration); WWII ⫽ World War II
Introduction
Multiple sclerosis is an inflammatory demyelinating disorder
of the CNS that affects individuals in their most productive
ages and is a tremendous burden for years to come. Defining
the natural history of this disease will help in making rational
treatment decisions and assist in unravelling its aetiology. In
seven previous papers, we explored the epidemiology of
multiple sclerosis using an unusually large cohort of multiple
sclerosis cases and pre-illness matched controls comprising
US veterans of World War II (WWII) and the Korean Conflict
(KC) (Kurtzke et al., 1979, 1985, 1992; Norman et al., 1983;
Page et al., 1993, 1995a; Kurtzke and Page, 1997). In
this report, we examine the long-term survival experience
following multiple sclerosis among WWII veterans.
The US veteran population is an exceptional resource for
the study of disease. It comprises a very large population
well indexed at many points of medical interest, and with
© Oxford University Press 2000
the potential for long-term follow-up study that is unparalleled
in the US. During WWII, 16 million young men and women
served in the military, where medical care was available
without regard to prior residence or socioeconomic status
(SES). A diagnosis of multiple sclerosis made one ineligible
for military service so that cases discovered in service were
at or near clinical onset. Furthermore, whenever the diagnosis
was entertained in the service, neurological evaluation was
unusually thorough as the diagnosis was cause for medical
discharge, which also made individuals eligible for serviceconnected disability care and compensation. After discharge
from the military, veterans with service-connected disabilities
were eligible for later medical care within the Department
of Veterans Affairs health system, again without regard to
prior residence or SES.
A number of studies have been published defining the
1678
M. T. Wallin et al.
survival characteristics of multiple sclerosis patients
(Bramwell, 1917; Brain, 1936; Ipsen, 1950; Carter et al.,
1950; Lazarte, 1950; Leibowitz et al., 1969; Kurtzke
et al., 1970; Visscher et al., 1984; Phadke et al., 1987; Riise
et al . 1988; Poser et al., 1989; Wynn et al., 1990; Miller
et al., 1992; Sadovnick et al., 1992; Brønnum-Hansen et al.,
1994; Midgard et al., 1995; Kantarci et al., 1998). More
recent cohorts have shown improved survival with mean
survival figures of ⬎25 years (Phadke et al., 1987; Riise
et al., 1988; Poser et al., 1989; Kantarci et al., 1998). The
question to be addressed in this report is whether the risk
factors that influence the diagnosis of multiple sclerosis also
play a significant role in survival subsequent to multiple
sclerosis. Regarding such risk factors, we earlier reported
that multiple sclerosis was most common in the northern tier
states, intermediate in the middle tier and lowest in the
southern tier (Kurtzke et al., 1979). White women had
roughly twice the risk of multiple sclerosis as white men,
with black men having half the risk of white men, regardless
of geography (Kurtzke et al., 1979). Age at multiple sclerosis
onset was found to be youngest in the northern tier states
and oldest in the southern tier (Kurtzke et al., 1992). We
also found striking correlations of population ancestry with
multiple sclerosis risk, especially for Swedish/Scandinavian
ancestry, even when controlling for the effects of latitude
(Page et al., 1993, 1995a). In a multivariate analysis, latitude,
years of education, urban versus rural address, high SES and
poor visual acuity at induction were all significant risk factors
for developing multiple sclerosis among white male WWII,
black male WWII and white male KC veterans (Kurtzke and
Page, 1997)
There has been disagreement between studies regarding
risk factors for survival after multiple sclerosis. Variables
that have differed include age at onset, sex, geographic
latitude and onset symptoms. Thus, studies of the relationships
between acknowledged multiple sclerosis risk factors and
multiple sclerosis survival have produced uneven results.
Here we examine the effects of such factors on survival
subsequent to multiple sclerosis in US veterans.
Patients and methods
The entire series has been described in detail earlier (Kurtzke
et al., 1979) and consists of 5305 US veterans of WWII or
the KC who were judged by the Department of Veterans
Afffairs as ‘service-connected’ for multiple sclerosis. Such a
decision for this disease required definitive evidence of
clinical signs attributable to multiple sclerosis during or since
~1960 within 7 years after military service, and was made
without regard to rank, race, sex or financial status. About
half the cases were ascertained from the 1956 Veterans
Affairs Medical Center (VA) roster of service-connected
cases, when the presumptive period for service connection
was 2 years after discharge. The remainder were ascertained
from the 1969 VA roster, by which time the presumptive
period had been extended to its (current) post-service interval
of 7 years. In this report, only cases ascertained in 1956
were assessed in order to minimize the interval between
onset and entry into the service. Each multiple sclerosis
patient was matched to a military control using year of birth,
date of entry into and branch of series, and survival of the
war. A random sample of 80 cases was reviewed for diagnosis
(J.F.K.), and 96% met all criteria of the Schumacher Panel
for definite multiple sclerosis (Schumacher et al., 1965).
All materials were abstracted from the military records of
the subjects.
Race and sex for each war cohort are represented here by
three sex–race groups: white women, white men and black
men. There were insufficient numbers of black women and
subjects of other races to permit their study. Although data
on entry into active duty (EAD) are available for all, data
on other risk factors were not abstracted for all subjects
because of financial strictures. We obtained such material for
all women and all non-white cases. For white male subjects,
risk factor data were gathered only for migrants (persons
born in one geographic tier—north, middle or south, who
entered military service in another) and for a 12.5% (i.e.
1 in 8) random sample of non-migrants (Kurtzke et al., 1979,
1985). Thus the sampling weight for white female, black
male and white male migrants was one, and the sampling
weight for white male non-migrants was eight. Latitude of
residence at EAD was abstracted from the subjects’ military
records, as was information to calculate the SES score. The
SES score was based on occupation and education and coded
according to the Bureau of the Census Standards (US Bureau
of the Census, 1963). Age at onset was abstracted from either
the military record or from VA compensation records. For
graphing purposes, age at onset was categorized into two
age groups: 艋25 years and 艌26 years.
Using these sampling weights yields a maximum effective
sample of 2489, reduced because of missing data to 2038
when socioeconomic data were examined. Survival is shown
for the first 50 years after onset. When analyses were based
on sampled data (e.g. all the Cox proportional hazards
analyses), weighted analyses were performed. In the few
instances in which data were available for all subjects (e.g.
analyses were limited to sex, race and EAD tier), unweighted
analyses were performed; this is the case for relative survival
rates by race and EAD tier and for standardized mortality
ratios (SMRs) by race and sex.
Vital status was ascertained to June 1996 by using the VA’s
Beneficiary Identification and Records Locator Subsystem.
Mortality from all causes was used as the outcome
measurement and not just death from multiple sclerosis. A
recent study of death reporting in WWII twins indicates that
the VA receives notice of death ~95% of the time (Page
et al., 1995b). For veterans receiving compensation, as is the
situation for these multiple sclerosis cases, it is likely that
mortality reporting is virtually complete.
All analyses were performed using the Statistical Analysis
System (SAS) computer software (SAS Institute, 1988).
PROC PHREG was used to fit multivariable Cox proportional
Epidemiology of multiple sclerosis in US veterans
Table 1 Sample sizes and mortality statistics, by race and sex
Race–sex group
Number
followed
Crude mortality
in % (no. of deaths)
White female
Black male
White male
Totals
92
79
2318
2489
68.5 (63)
78.5 (62)
83.4 (1934)
82.7
hazards models to the survival data. This procedure does not
require any assumptions about the particular shape of the
survival distribution (e.g. exponential or Weibull), but does
require an assumption that the ratio of the hazard functions
for any two individuals is constant (i.e. their hazards are
proportional); this latter assumption is subject to statistical
testing. Most important for our analysis is the fact that
Cox proportional hazard models can be used for univariate
analyses of risk factors as well as multivariate analyses that
yield estimates of risk factor effects adjusted simultaneously
for the effects of all other risk factors in the model.
Additionally, the Cox proportional hazards models allow for
left truncation (i.e. staggered entry into the cohort), which is
the case when every individual is followed from his or her
year of onset.
The multiple sclerosis cases in this analysis were accessed
from the VA compensation files, as of 1956. For the Cox
regression analysis, however, we calculated survival from a
more clinically meaningful base date, year of first symptom
onset. To do this, we limited post-onset survival only to
observed survival, which begins only when the case was
actually accessed. This is accomplished by excluding all
periods of unobserved survival from the analysis (e.g. if
onset were in 1945 and accession in 1956, the period from
1945 to 1955). PROC PHREG permits such exclusions.
Given the suggestion by Sigrid Poser (Poser et al., 1989)
that survival differences among subgroups of multiple
sclerosis patients may actually reflect demographic
differences, rather than disease processes, both relative
survival rates and SMRs were calculated. Because of small
samples in white females and black male groups, these
relative survival rates were interpolated between years when
either case or control rates were unchanged. SMRs provide
a comparison of multiple sclerosis case mortality with the
mortality of the entire US general population, rather than
just military veterans. SMRs were calculated by using the
software package OCMAP Plus (Marsh et al., 1998). The
starting point was the base date of 1956 (case accession date)
rather than onset date.
Results
Table 1 shows effective (i.e. weighted) sample sizes, and
crude mortality rates by sex and race groups. Crude mortality
rates are 68.5, 78.5 and 83.4%, respectively, for white
females, black males and white males. The three crude rates
are statistically different [χ2(2) ⫽ 11.07, P ⫽ 0.004], but the
1679
only statistically significant individual rates are for white
females and white males [χ2(1) ⫽ 10.68, P ⫽ 0.001]; in
particular, crude mortality rates for black males and white
males are not statistically different [χ2(1) ⫽ 1.345, P ⫽ 0.25].
Figure 1 shows 50-year survival subsequent to multiple
sclerosis onset for white females, white males and black
males. Median survival times are ~43 years for white females,
30 years for black males and 34 years for white males. White
female survival remains uniformly higher than both white
male and black male survival, while white male and black
male survival curves are much closer together, crossing
twice in the 50-year interval. Thus, the survival distribution
generally reflects the crude mortality rates. Figures 2–4 show
similar data for each of the single factors age at onset, EAD
tier and SES, respectively. Multiple sclerosis cases with
older age at onset have lower survival rates throughout the
50-year period (Fig. 2), while survival rates by EAD tier
(Fig. 3) do not appear to differ. Although survival rates by
SES show some overlap (Fig. 4), multiple sclerosis cases
with low SES do have a higher survival rate than cases with
high SES throughout the entire 50-year follow-up. This trend
was statistically significant.
Having examined the individual effects of various factors
on multiple sclerosis survival, we then proceeded to a
multifactorial analysis in which the effects of each
independent factor are adjusted for all the others. The results
of this analysis are shown in Table 2 as risk ratios. Age at
onset (measured in years), sex and SES each had independent
and significant effects on multiple sclerosis survival; neither
race nor EAD tier had a significant effect. Removing race
and EAD tier from the analysis resulted in a reduced model,
also shown in Table 2. In the full model, each year of
additional age at onset increases the risk of mortality by 1.07
(i.e. for 5 years, the increased risk is 1.38), males have a 1.8
higher mortality risk than females, and each additional higher
SES class increases mortality risk by ~5%.
We then examined relative survival, which was calculated
by dividing multiple sclerosis case survival rates by veteran
control survival rates for subjects in the various sex, race,
EAD and SES categories. A value of 1.00 indicates that
multiple sclerosis cases and veteran controls have the same
survival, while a value of 0.5, for example, would indicate
that multiple sclerosis cases had exactly one-half the survival
of veteran controls. Relative survival begins at 1.00 (i.e.
cases and controls have equal survival) and declines more
or less steadily as follow-up progresses. Figure 5 shows
relative survival by sex and race group. Except at
commencement of follow-up, multiple sclerosis cases always
have poorer survival than their veteran counterparts. By 20
years after the accession date, white male case survival is
only about two-thirds of that for white male veteran controls,
while after 40 years, white male relative survival is closer
to one-third. Although white females maintain a relative
advantage in survival over white males for the entire time
period, black male relative survival begins close to white
male relative survival, dips below it and then exceeds it at
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M. T. Wallin et al.
Fig. 1 Survival in multiple sclerosis cases, by race and sex.
Fig. 2 Survival in multiple sclerosis cases, by age at onset.
~30 years. The meandering black male relative survival curve
is in part due to small sample size. White male survival rates
do not differ significantly by EAD tier (Fig. 6), but relative
survival is uniformly higher among multiple sclerosis cases
from the southern tier, compared with northern tier cases.
Likewise, white male relative survival rates stratified by
SES show a statistically significant divergence, with high
SES doing worse for much of the follow-up, but are quite
close together at the end of follow-up (Fig. 7).
SMRs have the advantage of using a very large control
group, the US general population, but the disadvantage that
the population rates are available for only broad demographic
categories. Thus, for example, we can compare death rates
for white male multiple sclerosis cases with rates for all US
white males, but not all US veteran white males, or all high
SES veteran white males. Figure 8 shows SMRs for multiple
sclerosis cases by race and sex group. Except for black males
in the last decade, SMRs for all race and sex groups are
Epidemiology of multiple sclerosis in US veterans
1681
Fig. 3 Survival in multiple sclerosis cases, by EAD tier.
Fig. 4 Survival in multiple sclerosis cases, by socioeconomic class.
⬎100 for the entire follow-up period of 40 years. There is
an apparent tendency for SMRs to be greatest in the earlier
follow-up years and to decline over time. In the final decade
of follow-up, black male cases actually have better survival
than black males of comparable age in the general population.
Discussion
Survival is a fundamental measure of disease severity. Ideally,
it is best measured prospectively, from disease onset, and
within a defined population. In the US, there have been two
such population bases that have used this approach: Rochester,
Minn. (Wynn et al., 1990) and the US armed forces (Kurtzke
et al., 1970). A handful of other studies have utilized an
incident cohort to study survival. Retrospective surveys, on
the other hand, are hazardous and unreliable in the absence
of some guarantee that incidence, and the sampling ratio,
remain unchanged over the calendar period of estimation.
For example, if the series is increasing in size, it will be
biased toward early deaths.
1682
M. T. Wallin et al.
Table 2 Proportional hazards analysis of multiple sclerosis risk factors for death: full and
reduced models
Risk factor
Risk ratio
full model
Risk ratio
reduced model
Age at 1956
Age at onset of multiple sclerosis (per year)
Sex (male versus female)
Race (black versus white)
EAD tier†
Socioeconomic status‡
0.993
1.073*
1.782*
0.965
0.958
1.048*
–
1.067*
1.779*
–
–
1.047*
⬍ 0.001. †EAD is entry into active duty; risk is for each movement of a single tier northward (i.e. south
to middle or middle to north within the continental US). ‡Per each higher socioeconomic class level (total
of five).
*P
Fig. 5 Relative survival by race and sex.
Most studies published prior to the 1960s regarding the
survival period after onset of multiple sclerosis reported time
frames ⬍17 years (Bramwell, 1917; Brain, 1936; Ipsen,
1950; Carter et al., 1950; Lazarte, 1950). These series were
hospital-based with a bias towards the most severely affected
patients. They were also performed during the preantibiotic era.
The original survival experience of the WWII Army
hospital cohort showed a 25-year survival after onset of
disease of 69% (Kurtzke et al., 1970). The survival
curves were similar to those observed in a Mayo Clinic study
(25-year survival 74%) (Percy et al., 1971) and the Lower
Saxony study (25-year survival 63%) (Poser et al., 1989).
The results of our study with median survival ranging
between 30 and 43 years are in line with other recent incident
studies of multiple sclerosis survival. Median survival from
disease onset in a German epidemiological series ranged
between 35 and 42 years without any significant difference
between the sexes (Poser et al., 1989). Brønnum-Hansen
reported a median survival of 33 years for men and 28 years
for women in a large Danish population cohort (BrønnumHansen et al., 1994). Finally, Riise reported the survival
experience of a Norwegian incident cohort with a median
survival of 27 years (Riise et al., 1988). This shorter survival
figure is in part biased as date of diagnosis of multiple
sclerosis was taken as the starting date and not time of the
first symptom onset. Interestingly, survival rates improved in
cohorts with more recent onset of multiple sclerosis in the
Danish (Brønnum-Hansen et al., 1994) and Norwegian (Riise
et al., 1988) studies but not in the Rochester study (Wynn
et al., 1990). The interval between first symptom onset and
diagnosis is ~4 years in Rochester (Wynn et al.,1990).
Our crude 40-year survival rates are lower than the nearly
40-year rates in the Danish multiple sclerosis population
Epidemiology of multiple sclerosis in US veterans
1683
Fig. 6 Relative survival by EAD tier (white males only).
Fig. 7 Relative survival by socioeconomic class (white males only).
study (39% females and 25% males). The differences may
be explained by better medical care and better access to
medical care in Denmark, the higher proportion of females
in the Danish cohort and a relatively high proportion of
‘possible multiple sclerosis’ cases (16.8%), if this last
included other, less severe, neurological diseases. Three
agents were approved for relapsing–remitting multiple
sclerosis by the Federal Drug Administration between 1993
and 1996 [interferon-β 1b (1993), interferon-β 1a (1996)
and glatiramer acetate (1996)]. It is unlikely that many
veterans in the cohort were exposed to these immunomodulating medications. A lottery prevented wide access to
interferon-β 1b when it was introduced initially in 1993, and
the other two agents became available the year that followup was terminated.
Other multiple sclerosis survival studies have not, to our
knowledge, addressed the variables of race or SES, both
significant risk factors in developing multiple sclerosis. While
black males tended to have significant survival risks somewhere between white males and white females in the actuarial
1684
M. T. Wallin et al.
Fig. 8 SMRs for multiple sclerosis cases by sex and race.
analysis, race was not a significant variable in the Cox
regression analysis.
Comparison of the survival experience in our multiple
sclerosis cohort was done with the US veteran population
(utilizing relative survival) and the US general population
(utilizing SMRs). Relative survival rates did not appear to
differ by race or sex groups (Fig. 5). This was, in part, due
to the small sample sizes for black males and white females
which produced unstable estimates. Nonetheless, at 40 years
post-multiple sclerosis onset, white male survival was less
than that of both black males and white females. Examining
relative survival by EAD tier in white males revealed no
significant differences between rates, but there was a general
trend for improved survival in the southern compared with
the northern tier. The SMR data for all race–sex groups
showed a gradual downward trend (Fig. 8). This trend reflects
a higher risk for death in multiple sclerosis patients early on
in the disease and a competing burden of death in the general
population with time, thereby reducing the SMR. There were
significant differences in relative survival by SES class among
white males. Lower SES classes had a longer survival than
higher SES classes. The major purpose for comparing our
cohort with both the US and veteran controls was to contrast
the unique survival experiences of both populations and
also to allow us to compare our cohort with those from
other studies.
Veteran survival is better than that of the US population
as a whole. This has been described as the ‘healthy soldier
effect’, denoting the fact that the military screens out
applicants with health problems that would preclude them
from performing rigorous physical duties. Nefzger calculated
age standardized mortality ratios for WWII veterans between
the years 1946 and 1965 (Nefzger, 1970). The observed
mortality was 16% below expectation over the 20-year period.
A more recent mortality study utilizing the Persian Gulf
War veterans and other non-deployed veterans showed that
adjusted SMRs were 0.38 and 0.44, respectively (Kang et al.,
1996). Both ratios are well below the mortality of the general
US population, but the latter especially is of rather short
duration. It has been postulated that the ‘healthy soldier
effect’ ultimately disappears. The ‘healthy soldier effect’
probably has had a favourable effect on the survival
experience of the current study cohort as compared with the
general US population. Our total age-adjusted SMR was
2.18. This figure is similar to the total SMR figure of 2.0
from a large Canadian multiple sclerosis cohort (Sadovnick
et al., 1992) and smaller than 3.25 (95% confidence interval:
3.11–3.38) from a large Danish multiple sclerosis cohort
(Brønnum-Hansen et al., 1994). The causes of death in the
current veteran cohort will be the subject of a future report.
Regarding risk factors for survival, we found that some of
the factors which influence the development of multiple
sclerosis have no significant influence on survival after
multiple sclerosis. These factors include race and EAD tier.
We did, however, find that female sex, lower SES and
younger age at onset of multiple sclerosis significantly
improved survival. Neither race nor EAD tier was
significantly associated with survival after multiple sclerosis
onset (Table 2).
As in the Israeli (Leibowitz et al., 1969), Danish
(Brønnum-Hansen et al., 1994), Rochester (Wynn et al.,
1990) and Lower Saxony (Poser et al., 1989) studies, we
Epidemiology of multiple sclerosis in US veterans
1685
Table 3 Some multiple sclerosis survival studies with corresponding risk factors
Study
Last
year of
study
Country
Total
cases
Age SES Race Sex Dis- Resi- PolyCere- Brain- Motor Sens.
at
ability dence regional bellar stem
onset
Leibowitz et al.
Kurtzke et al.
Visscher et al.
Phadke et al.
Riise et al.
Poser et al.
Wynn et al.
Miller et al.
Sadovnick et al.
Brønnum-Hansen et al.
Midgard et al.
Current study
1967
1963
1980
1980
1986
1981
1984
1983
1991
1986
1991
1996
Israel
USA
USA
UK
Norway
Germany
USA
New Zealand
Canada
Denmark
Norway
USA
266
527
941
1055
598
224/1429
206
107
2348
6727
251
2489
⫹/⫺
NS
⫹
⫹
⫹
⫹
⫹
NS
NS
NS
⫹
⫹
⫹
⫹
⫹
⫹
NS
⫹
⫹
⫹
NS
⫹
ON Sphinc- Clin
ter
course
NS
⫹
⫹
⫹
⫹
⫹
NS
⫹
NS
⫹
NS
NS
NS
NS
NS
NS
NS
NS
NS
⫹
⫹
NS
⫹
⫹
⫹
⫹
⫹
NS
⫹
⫹
⫹
NS
⫹
⫹
⫹
⫹
NS
ON ⫽ optic neuritis; NS ⫽ not significant.
saw higher survival in females and lower survival in lateonset cases. However, unlike the Norwegian (Riise et al.,
1988; Midgard et al., 1995), and Western US (Visscher et al.,
1984) studies, we found this significant difference in survival
by sex even after adjusting for other covariates, in particular
age at onset. In addition, unlike the Western US (Visscher
et al., 1984) study, we found no significant effect of latitude
on survival. One could argue that there is a clinically
significant improved survival for multiple sclerosis patients
in the southern EAD tier based on the relative survival
curves, despite the fact that EAD tier was not a significant
risk factor in the Cox proportional hazard model.
Other multiple sclerosis survival studies have not, to our
knowledge, evaluated the risk factor SES. Low SES was
found to be a significant predictor of improved survival in
the Cox model. This initially would appear counter-intuitive
as one would expect those with higher SES to be more
equipped to provide more effectively for their health care
needs and survive longer than those individuals categorized
as low SES. The medical literature has shown a powerful
connection between low SES and mortality for a number of
major diseases (Lynge, 1997; McCally et al., 1998; Kunst
et al., 1998). Even within industrialized societies, where none
would be considered poor by comparison with developing
countries, there appears to be a social gradient in mortality
(Marmot and Feeney, 1997). This suggests that there are
factors that operate across the whole of society that influence
mortality risks. There are likely to be confounding variables
such as ethnicity and race that may explain some of the
survival risk from high SES in our study. For example, whites
who are more highly educated, earn high incomes and are
non-manual workers may be more likely to be of Scandinavian
ethnicity. Ethnicity, therefore, may be confounding the
relationship between SES and survival. Race (black versus
white) was not found to be a significant predictor of survival
in the univariate or multivariate models (Table 2), however.
Because SES was a significant risk factor in both models of
Table 2, it is unlikely that its effect is due to confounding
by race. Specifically, although the full model adjusted for
race and the reduced model did not, the presence or absence
of race in the model had virtually no impact on the estimate
of the effect of SES: 1.048 in the full model versus 1.047 in
the reduced model. Alternatively, small numbers of nonwhite multiple sclerosis subjects and, therefore, limited power
may be an explanation for this lack of significance. One
interpretation of the SES data is that high SES is a precipitant
for disease and for severity. This would suggest a subclinical
state, which can be worsened to produce disease, and
worsened further to result in death by some correlate of high
SES. However, sex, race and geography do not support this
interpretation.
Table 3 lists multiple sclerosis cohort studies that have
reported risk factors for survival. The studies of Kurtzke,
Riise, Poser, Wynn, Sadovnick, Brønnum-Hansen and
Midgard were prospective in nature and involved incident
cases. Other studies were based on prevalence surveys. The
studies listed had different diagnostic criteria for multiple
sclerosis, variable sample sizes and variable lengths of followup. Risk factors that tended to be in agreement across studies
included age at onset of multiple sclerosis, with virtually all
studies reporting that later age of onset of multiple sclerosis
was associated with shorter survival compared with earlier
onset. The exception to this was the study by Kurtzke
showing a non-significant effect of age at onset on surviving
the first 20 years of the follow-up. This finding is largely
related to the young age of the cohort, with 58% of cases
having onset between ages 20 and 29 years. Other risk factors
that were in agreement across studies and predicted worse
survival included: high initial disability scores, and
progressive disease course.
In summary, our study showed that life expectancy in
veterans with multiple sclerosis is significantly reduced
compared with the US general population, but the difference
lessens over time. Survival compared with veterans continued
to worsen with follow-up time. Female sex, low SES and
younger age at onset significantly improved survival in
this cohort. Future studies hopefully will better clarify the
1686
M. T. Wallin et al.
relationships between race, sex, SES, ethnic background and
survival in multiple sclerosis.
Leibowitz U, Kahana E, Alter M. Survival and death in multiple
sclerosis. Brain 1969; 92: 115–30.
Lynge E. Unemployment and cancer: a literature review. [Review].
IARC Sci Publ 1997; 138: 343–51.
Acknowledgements
Presented at the 1997 American Neurological Association
Convention in San Diego, CA and the 1997 Society for
Epidemiologic Research Convention in Edmonton, Alberta.
This study was supported by Department of Veterans Affairs
contract numbers V688P-1532 and V688P-1997 (Neuroepidemiology Research Program, VAMC Washington, DC)
to the National Academy of Sciences.
References
Brain WR. Prognosis of disseminated sclerosis. Lancet 1936; 2:
866–7.
Bramwell B. The prognosis in disseminated sclerosis: duration in two
hundred cases of disseminated sclerosis. Edinb Med J 1917; 18: 16–23.
Brønnum-Hansen H, Koch-Henriksen N, Hyllested K. Survival of
patients with multiple sclerosis in Denmark: a nationwide, long-term
epidemiologic survey. [Review]. Neurology 1994; 44: 1901–7.
Carter S, Sciarra D, Merritt HH. The course of multiple sclerosis as
determined by autopsy proven cases. Assoc Res Nerv Ment Dis Proc
1950; 28: 471–511.
Ipsen J Jr. Life expectancy and probable disability in multiple
sclerosis. N Engl J Med 1950; 243: 909–13.
Kang HK, Bullman TA. Mortality among U.S. veterans of the Persian
Gulf War. N Engl J Med 1996; 335: 1498–504.
Kantarci O, Siva A, Eraksoy M, Karabudak R, Sutlas N, Agaoglu J,
et al. Survival and predictors of disability in Turkish MS patients.
Neurology 1998; 51: 765–72.
Kunst AE, del Rios M, Groenhof F, Mackenbach JP. Socioeconomic
inequalities in stroke mortality among middle-aged men: an
international overview. European Union Working Group on
Socioeconomic Inequalities in Health. [Review]. Stroke 1998; 29:
2285–91.
Kurtzke JF, Page WF. Epidemiology of multiple sclerosis in US
veterans: VII. Risk factors for MS. Neurology 1997; 48: 204–13.
Kurtzke JF, Beebe GW, Nagler B, Nefzger MD, Auth TL, Kurland
LT. Studies on the natural history of multiple sclerosis. V. Long-term
survival in young men. Arch Neurol 1970; 22: 215–25.
Kurtzke JF, Beebe GW, Norman JE Jr. Epidemiology of multiple
sclerosis in US veterans: 1. Race, sex, and geographic distribution.
Neurology 1979; 29: 1228–35.
Kurtzke JF, Beebe GW, Norman JE Jr. Epidemiology of multiple
sclerosis in US veterans: III. Migration and the risk of MS. Neurology
1985; 35: 672–8.
Kurtzke JF, Page WF, Murphy FM, Norman JE Jr. Epidemiology of
multiple sclerosis in US veterans: IV. Age at onset.
Neuroepidemiology 1992; 11: 226–35.
Lazarte JA. Multiple sclerosis: prognosis for ambulatory and
nonambulatory patients. Assoc Res Nerv Ment Dis Proc 1950; 28:
512–23.
Marmot M, Feeney A. General explanations for social inequalities in
health. [Review]. IARC Sci Publ 1997; 138: 207–28.
Marsh GM, Youk AO, Stone RA, Sefcik S, Alcorn C. OCMAP-PLUS:
a program for the comprehensive analysis of occupational cohort data.
J Occup Environ Med 1998; 40: 351–62.
McCally M, Haines A, Fein O, Addington W, Lawrence RS, Cassel
CK. Poverty and ill health: physicians can, and should, make a
difference. [Review]. Ann Intern Med 1998; 129: 726–33.
Midgard R, Albrektsen G, Riise T, Kvale G, Nyland H. Prognostic
factors for survival in multiple sclerosis: a longitudinal, population
based study in Møre and Romsdal, Norway. J Neurol Neurosurg
Psychiatry 1995; 58: 417–21.
Miller DH, Hornabrook RW, Purdie G. The natural history of multiple
sclerosis: a regional study with some longitudinal data. J Neurol
Neurosurg Psychiatry 1992; 55: 341–46.
Nefzger MD. Follow-up studies of World War II and Korean War
prisoners: I. Study plan and mortality findings. Am J Epidemiol 1970;
91: 123–38
Norman JE Jr, Kurtzke JF, Beebe GW. Epidemiology of multiple
sclerosis in US veterans: 2. Latitude, climate and the risk of multiple
sclerosis. J Chronic Dis 1983; 36: 551–9.
Page WF, Kurtzke JF, Murphy FM, Norman JE Jr. Epidemiology of
multiple sclerosis in US veterans: V. Ancestry and the risk of multiple
sclerosis. Ann Neurol 1993; 33: 632–9.
Page WF, Mack TM, Kurtzke JF, Murphy FM, Norman JE Jr.
Epidemiology of multiple sclerosis in US veterans: VI. Population
ancestry and surname ethnicity as risk factors for multiple sclerosis.
Neuroepidemiology 1995a; 14: 286–96.
Page WF, Braun MM, Caporaso NE. Ascertainment of mortality in
the US veteran population: World War II veteran twins. Mil Med
1995b; 160: 351–5.
Percy AK, Nobrega FT, Okazaki H, Glattre E, Kurland LT. Multiple
sclerosis in Rochester, Minn. A 60-year appraisal. Arch Neurol 1971;
25: 105–11.
Phadke JG. Survival pattern and cause of death in patients with
multiple sclerosis: results from an epidemiological survey in northeast
Scotland. J Neurol Neurosurg Psychiatry 1987; 50: 523–31.
Poser S, Kurtzke JF, Poser W, Schlaf G. Survival in multiple sclerosis.
J Clin Epidemiol 1989; 42: 159–68.
Riise T, Grønning M, Aarli JA, Nyland H, Larsen JP, Edland A.
Prognostic factors for life expectancy in multiple sclerosis analysed
by Cox-models. J Clin Epidemiol 1988; 41: 1031–6.
Sadovnick AD, Ebers GC, Wilson RW, Paty DW. Life expectancy in
patients attending multiple sclerosis clinics. Neurology 1992; 42:
991–4.
SAS Institute. SAS® procedures guide, release 6.03 edition. Cary
(NC): SAS Institute, 1988.
Epidemiology of multiple sclerosis in US veterans
Schumacher GA, Beebe GW, Kibler RF, Kurland LT, Kurtzke JF,
McDowell F, et al. Problems of experimental trial of therapy in
multiple sclerosis: report by the panel on the evaluation of
experimental trials of therapy in multiple sclerosis. Ann NY Acad Sci
1965; 122: 552–68.
US Bureau of the Census. Methodology and scores of socioeconomic
status. Working Paper No. 15. Washington (DC): United States Bureau
of the Census; 1963.
Visscher BR, Liu K-S, Clark VA, Detels R, Malmgren RM, Dudley JP.
1687
Onset symptoms as predictors of mortality and disability in multiple
sclerosis. Acta Neurol Scand 1984; 70: 321–8.
Wynn DR, Rodriguez M, O’Fallon MW, Kurland LT. A reappraisal of
the epidemiology of multiple sclerosis in Olmsted County, Minnesota.
Neurology 1990; 40: 780–6.
Received January 6, 2000. Revised March 23, 2000.
Accepted March 23, 2000