Journal of Clinical Densitometry, vol. 9, no. 1, 22–30, 2006
Ó Copyright 2006 by The International Society for Clinical Densitometry
1094-6950/06/9:22–30/$32.00
DOI: 10.1016/j.jocd.2006.05.004
Position Statement
Application of the 1994 WHO Classification to Populations
Other Than Postmenopausal Caucasian Women: The 2005
ISCD Official Positions
William D. Leslie,1 Robert A. Adler,2 Ghada El-Hajj Fuleihan,3 Anthony B. Hodsman,4
David L. Kendler,5 Michael McClung,6 Paul D. Miller,7 and Nelson B. Watts8
1
3
University of Manitoba, Winnipeg, Manitoba, Canada; 2McGuire Veterans Affairs Medical Center, Richmond, VA;
American University of Beirut, Beirut, Lebanon; 4University of Western Ontario, London, Ontario, Canada; 5University
of British Columbia, Vancouver, British Columbia, Canada; 6Oregon Osteoporosis Center, Portland, OR; 7Colorado
Center for Bone Research, Lakewood, CO; and 8University of Cincinnati, Cincinnati, OH
Abstract
In 2003, the International Society for Clinical Densitometry (ISCD) developed Official Positions regarding the
applicability of the World Health Organization (WHO) classification of bone mineral density to populations other
than postmenopausal women. However, these prior Official Positions do not fully address bone mineral density reporting in females prior to menopause, men, and non-whites. During the 2005 ISCD Position Development Conference, members of the ISCD Expert Panel in conjunction with the ISCD Scientific Advisory Committee re-addressed
these topics and, based upon stringent reviews of best available data, developed ISCD Official Positions that provide
greater specificity and clarification with respect to the following: (1) the utility of the term ‘osteopenia’; (2) utilization of T- and Z-scores for bone mineral density reporting; (3) when to apply the WHO densitometric classification; and (4) which normative database(s) should be used for non-white individuals. Briefly, the term ‘‘osteopenia’’
is retained, but ‘low bone mass’ or ‘low bone density’ is preferred. Z-scores, not T-scores, are preferred in females
prior to menopause and males under age 50. In these individuals, a Z-score of 22.0 or lower is defined as ‘‘below the
expected range for age’’ and a Z-score above 22.0 is ‘‘within the expected range for age.’’ T-scores are preferred and
the WHO classification is applicable for postmenopausal women and men age 50 and older. These Official Positions,
rationale and evidence are discussed in the following report.
Key Words: Densitometry; osteoporosis; official positions; dual-energy X-ray absorptiometry; DXA.
These criteria have subsequently been applied to assessment
of fracture risk, diagnostic classification, and treatment initiation in individuals. The WHO Technical Report intended
these categories to be applied only to postmenopausal white
(Caucasian) women. This has created uncertainty in diagnosing osteoporosis in other groups such as males, females prior
to menopause, and non-whites, who together vastly outnumber postmenopausal white women. The general acceptance
of the WHO diagnostic criteria was a sentinel event in the
worldwide recognition of osteoporosis as a major public
health concern. The International Society for Clinical Densitometry (ISCD) has addressed the limitations of the WHO
Introduction
The ability to easily assess bone mineral density (BMD)
revolutionized the clinical approach to osteoporosis. This
was recognized in the World Health Organization (WHO)
definition for osteoporosis as ‘‘a systemic skeletal disease
characterized by low bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone
fragility and susceptibility to fractures’’ (1). Although BMD
is recognized as a continuous risk factor for fracture (i.e.,
no fracture threshold exists), operational ranges for the
T-score were proposed (Table 1) for epidemiologic purposes.
22
Application of the 1994 WHO Classification
Table 1
World Health Organization Criteria for Diagnosing
Osteoporosis Using Bone Density Measurements*,a
23
I. Use of the Term Osteopenia: Should
it Remain in the Densitometry Lexicon?
ISCD Official Position
Category
T-score
Normal
21.0 or greater
Osteopenia
Between 21.0 and 22.5
Osteoporosis
22.5 or less
Severe or established osteoporosis
22.5 or less
and fragility fracture
*See reference (1).
a
Units are standard deviations above (positive) or below (negative) the young adult mean value.
diagnostic criteria in order to apply them to individual patients in clinical practice. New WHO initiatives to use
BMD T-scores together with clinical risk factors to estimate
fracture probability will provide clinicians with an additional
tool to manage their patients (2).
The current ISCD Official Positions do not fully address
BMD reporting in females prior to menopause, men, and
non-whites (3–6). It is not explicitly stated whether young
men (age 20–50) should have BMD reported using T-scores,
as suggested for men 50 years of age and older, or Z-scores,
as suggested for females prior to menopause. The applicability of white reference data for non-white populations outside
of the United States is unclear. At the center of this issue is
the question of whether one can make a diagnosis of osteoporosis in these groups and, if so, how? The current report focuses on some of the limitations in the ISCD Official
Positions as they relate to BMD reporting in groups other
than postmenopausal white females. These recommendations
are necessarily based upon incomplete data and will undoubtedly evolve as the science matures.
These ISCD initiatives are not occurring in isolation. The
WHO Collaborating Centre for Metabolic Bone Diseases is
leading an international team (which includes the ISCD)
with the objective of developing a globally applicable measure of absolute fracture risk based upon multiple risk factors
including BMD (2). This could silence much of the controversy regarding choice of reference data for T-score calculation and usefulness of relatively arbitrary densitometric
categorizations (7–9).
Methodology
The methods used to develop, and grading system applied
to these ISCD Official Positions is presented in the Executive Summary that accompanies this paper. Briefly, all Positions were graded on quality of evidence (good, fair, poor),
strength of recommendation, and applicability (worldwide or
limited).
Journal of Clinical Densitometry
The term ‘‘osteopenia’’ is retained, but ‘‘low bone mass’’
or ‘‘low bone density’’ is preferred.
Grade: Poor-C-1
Rationale
The original purpose of the WHO classification was to provide a framework to allow collection of epidemiological data
(1). If the WHO classification was used only as intended, no
individual would be diagnosed with ‘osteopenia’ because the
label would only be applied to groups of people. Although
it was not intended that the WHO classification be applied
to individual patients, it works well to define ‘normal’
(T-score 5 21.0 and above) and ‘osteoporosis’ (T-score 5
22.5 and below). Several large studies have shown a high
risk of fracture in patients who have T-scores of –2.5 and below, and a significant reduction in fracture risk with treatment, making this threshold an ‘evidence-based’ criterion
for the diagnosis of osteoporosis and for the initiation of
treatment.
Discussion
Fracture risk is continuous; there is no ‘‘fracture threshold ’’
(7). Although it is sometimes useful to think categorically
when dealing with a continuous variable, the category of
‘‘osteopenia’’ creates problems in at least four ways. Firstly,
subjects in the upper part of this range could be perfectly
normal depending on their age. Applying a medical label
such as ‘‘osteopenia’’ to a healthy young person can create
considerable anxiety that may last lifelong. Secondly, subjects in the lower part of this range are almost as likely to
fracture as patients on the lower side of the arbitrary cut
point (potentially more likely to fracture, depending on other
risk factors for fracture). Apparently healthy patients in the
upper part of this range should usually be reassured and perhaps monitored periodically. Patients in the lower part of the
range should be monitored more frequently, and may even
be candidates for pharmacologic intervention, depending
on how low their BMD is and the presence of other risk factors (8). Thirdly, confusion has arisen due to the word ‘‘osteopenia’’ being commonly used by radiologists as
a qualitative term to describe the radiographic appearance
of bones, and not as a quantitative term as used by bone
densitometrists. Finally, patients confuse the term ‘‘osteopenia’’ with ‘‘osteoporosis’’ and often consider that the latter
is an equally serious medical disorder requiring treatment.
For these reasons, the term ‘‘osteopenia’’ is best avoided.
The descriptive term ‘‘low bone mass’’ or ‘‘low bone density’’ is preferred for people with T-scores between –1 and
–2.5. This terminology is adopted throughout the remainder
of this document.
Volume 9, 2006
24
Leslie et al.
Often ignored is the WHO category of ‘severe’ or ‘established’ osteoporosis, meant to apply to patients who have already fractured and have a T-score of 22.5 or less. Although
a fragility fracture, particularly a vertebral fracture, is a strong
predictor of future fracture, this is true whether the T-score is
–2.6 or –2.4. In fact, there is an apparent contradiction:
a larger number of patients who have fragility fractures
have T-scores above 22.5 (9). Although patients with a Tscore consistent with osteoporosis are at higher risk for fractures than those with low bone mass, there are so many more
patients with low bone mass that the number of women with
fractures in this category is higher. It is possible that some clinicians would not diagnose osteoporosis in a patient with
a fragility fracture because the T-score was above 2.5. A patient with low bone mass and fragility fracture may be more
likely to fracture in the future than a patient with WHO-defined osteoporosis but without a fragility fracture (10). Patients with a fragility fracture warrant a clinical diagnosis of
osteoporosis, have a high risk of future fracture, and should
be treated accordingly. Apparently healthy subjects in the upper range of ‘‘low bone mass’’ should be reassured and monitored periodically. Apparently healthy subjects in the lower
range of ‘‘low bone mass’’ deserve consideration of pharmacologic intervention. In brief, people with low bone mass or
density are not necessarily at high fracture risk and require
an individualized approach that considers the importance of
other risk factors, most importantly age and prevalent fractures.
II. BMD Reporting
ISCD Official Positions
In Females Prior to Menopause and in Males
Younger Than Age 50
Z-scores, not T-scores, are preferred. This is particularly
important in children.
Grade: Poor-C-1
A Z-score of 22.0 or lower is defined as ‘‘below the
expected range for age’’ and a Z-score above 22.0 is
‘‘within the expected range for age.’’
Grade: Poor-C-1
In Postmenopausal Women and in Men
Age 50 and Older
T-scores are preferred.
Grade: Fair-B-1
Rationale
The 2003 ISCD Official Positions (3) stated that for ‘‘Diagnosis in premenopausal women (age 20 to menopause) .
Z-scores rather than T-scores should be used.’’ For ‘‘diagnosis
in men . between age 50 and 65, T-scores may be used.’’ It
is implied but not explicitly stated that Z-scores be used
Journal of Clinical Densitometry
between the ages of 20 and 50 years. The ISCD recommendation to use Z-scores in young adults was, in part, intended to
avoid misapplication of WHO criteria, which are based upon
the T-score, to inappropriate populations (4). The WHO criteria were developed for postmenopausal white females, and
extrapolation to other groups may not identify people at
equivalent levels of fracture risk. In addition, it was felt that
the Z-score might be more appropriate for non-white populations since the T-score is not adjusted for race on many densitometers. The issue of normative databases for non-white
populations is dealt with elsewhere in this report. The use
of Z-scores in children is an absolute necessity since children
have not yet achieved peak bone mass and therefore T-scores
are meaningless (4).
Discussion
Is There Much Difference Between T-scores
and Z-scores in Younger Adults?
Assuming that bone density is relatively stable prior to age
50 (approximately the average age of menopause), there
should be only minor differences between T-scores and Zscores derived from ethnicity- and sex-matched reference
population. There is no compelling scientific basis, therefore,
for preferring one to the other in terms of bone density reporting. By extension, fracture outcomes cannot be used to adjudicate the choice and no other gold standard exists. The
choice of one method of reporting over the other must, therefore, be based upon other considerations as discussed below.
An assessment of the difference between T-scores and Zscores for major manufacturers (GE Healthcare, Hologic,
and Norland) and measurement sites (lumbar spine, total
hip, femoral neck, trochanter, 33% forearm) was undertaken
for a 20-year old and 50-year old white man and woman
(Table 2). As expected, in healthy young white adults (ages
20–50) there are relatively small differences between the respective T-score and Z-score for a given bone density measurement. At age 20, the difference between T-scores and Z-scores
varies from 10.2 to 20.2. At age 50, the difference between Tscores and Z-scores varies from 0.0 to 21.4, with a mean of
approximately 20.5. This means that at age 50, a Z-score of
22.0 is approximately equivalent to a T-score of 22.5. The
same general findings were seen with men and women.
Some differences were observed between equipment manufacturers. One contributing factor is the way of representing agerelated change in BMD, typically either a polynomial model
(quadratic or cubic) or linear model (bilinear or trilinear).
Standardization among manufacturers in the mathematical approach would be beneficial. The use of different reference populations is another source of known inter-manufacturer
variation (11). Standardization of hip measurements using
the National Health and Nutrition Examination Survey
(NHANES) III population (12) should reduce variation, but
not all practitioners select the NHANES III reference data option. Manufacturers are encouraged to complete the conversion of NHANES III reference data for all hip sites in both
genders.
Volume 9, 2006
Application of the 1994 WHO Classification
25
Table 2
Difference Between T-Score and Z-score (T Minus Z)
According to Site, Gender, Age, and Equipment
Manufacturer
Age 20
Age 50
GE Hologic Norland GE Hologic Norland
Software
Version
v8.8 V 101 Ver 2.9.0 v8.8 V 101 Ver 2.9.0
White Female
L1–L4
0 20.2
Femoral
10.1
0
neck
Total hip
10.1
0
Trochanter
10.1
0
33% Radius
0
0
White Male
L1–L4
0
0
Femoral
10.1
0
neck
Total hip
10.2
0
Trochanter
10.1
0
33% Radius
0
0
20.1 20.4 20.7
20.1 20.8 20.7
20.1
21.0
0
20.5 20.4
10.1 20.5 20.4
0
0 20.7
20.5
20.8
20.3
20.1 20.2 20.4
0
20.6 20.7
20.2
21.4
0
20.3 20.3
20.1 20.3 20.3
0
0 20.5
21.0
20.9
20.2
Note: Values are 60.1 due to rounding. Hip results based on
NHANES III where available.
Why Is BMD Testing Performed?
The initial measurement of BMD is usually performed for
one of two very different reasons: to assess fracture risk and to
assign a diagnostic classification. Older adults (postmenopausal women and men age 50 and older) may be at increased
risk for fracture. T-scores more appropriately reflect shortterm fracture risk than Z-scores, since Z-scores obscure the
‘normal’ age-related decline in bone mass which contributes
to, but does not fully account for, the age-related increase in
fractures. Conversely, determination of how an individual’s
BMD has been affected by a metabolic risk factor is optimized
by matching the reference population as closely as possible (at
least for age, sex, and ethnicity), implying use of the Z-score.
Weight-adjustment of the Z-score is an option that is available on some instruments. The ISCD has previously recommended that weight-adjusted Z-scores be disabled on the
software since their use will produce a more negative Z-score
in overweight individuals despite the fact that they are not at
greater fracture risk. Conversely, underweight individuals will
have a better Z-score despite the fact that low body weight
and body mass index are associated with greater risk for fracture (13,14). There are concerns regarding validation of the
methods used for the Z-score weight-adjustment, uncertainty
if the same adjustment applies to stable and changing weight,
and lack of standardization among manufacturers. On
balance, it is felt that the disadvantages of weight-adjusting
Z-scores outweigh any theoretical advantages.
Journal of Clinical Densitometry
Age is a strong predictor of fracture risk that is independent of BMD. Since healthy young adults have low shortterm fracture risk across a wide BMD spectrum (2,15,16),
the use of a T-score (or Z-score) diagnostic cutoff of 22.5
does not have the same significance in a 30-year-old as in
a 70-year-old. BMD measurement in healthy premenopausal
women and men younger than age 50 cannot be used to assess
short-term fracture risk and is only recommended to assess
the skeletal impact of specific conditions. Conceptually, the
Z-score is best suited to this purpose and avoids incorrectly
labeling patients according to WHO criteria. The strongest argument in favor of reporting T-scores in young adults is to
maintain a consistent approach across the age spectrum
from young adulthood to mid-life and beyond, but this is
not felt to outweigh the disadvantages.
For most biological variables that are normally distributed
(as is BMD), a ‘normal range’ or reference range is defined as
the normal mean plus or and minus 2.0 standard deviations
(SD). There is no compelling reason to define BMD differently than other variables. In other words, a 25-year-old
who has a Z-score of 21.9 is below average but still within
the expected range for age. Conversely, a Z-score that is 2.0
or more SD below the expected range for age should be considered abnormal.
III. Applicability of the WHO Densitometric
Classification
ICSD Official Position
In Postmenopausal Women and in Men
Age 50 and Older
The WHO densitometric classification is applicable.
Grade: Fair-B-1
Rationale
The progressively increasing fracture burden experienced
by women after menopause was the impetus for developing
the WHO densitometric classification. Bone quality may deteriorate with age but this is not captured in bone densitometry measures. Younger adults with reduced bone mass do not
have the same increased fracture risk as older adults with the
same bone mass. Therefore, it is important to carefully consider the implications of applying the WHO classification to
premenopausal women and men age 50 and older.
Discussion
Diagnostic Criteria and Clinical Recommendations
It is important not to confuse diagnostic thresholds with
intervention thresholds. Although the WHO densitometric
classification was explicitly designed for postmenopausal
females, it was never intended to be a recommendation for
the testing of all women at or after menopause, or that a Tscore in the osteoporosis range should be used as the sole basis for initiating treatment. Rather, the WHO criteria provided
a standardized basis for measuring and comparing the
Volume 9, 2006
26
frequencies of BMD in well-defined categories. The position
of the ISCD is that BMD testing be considered for all women
aged 65 and older and all men aged 70 and older, independent
of other risk factors. Testing in younger individuals can be
considered in the presence of other risk factors, though
BMD measurement is usually not indicated in females prior
to menopause or in men before age 50 years because of the
low prevalence of significantly decreased BMD and low fracture risk (15). In women, common risk factors for a low BMD
include premature menopause, chronic glucocorticoid therapy, family history of fragility fractures, and thin body habitus (17). In men, the three most common risk factors for low
BMD include alcohol abuse, hypogonadism, and glucocorticoid therapy (18).
Is the WHO Densitometric Classification Broadly
Applicable to Premenopausal Women and Younger
Men?
Use of the WHO criteria in younger women and men is
problematic since their actual fracture risk is much lower
than at an equal level of BMD for an older individual.
Whereas the 10-year fracture risk in a 70-year-old woman
with a T-score of 21.0 is 11.5%, that of a 45-year-old woman
with the same BMD would be three-fold lower, estimated at
4.3% (19). Similar conclusions are obtained by examining
the corresponding data in men (9). The 10-year probability
for sustaining an osteoporotic fracture (i.e., spine, hip, shoulder or vertebral) for a 45-year-old woman with a T-score of
22.5 at the hip is estimated at 8.1% (2). Such estimates increase to 16.2% in a 60-year-old woman, to 22.8% in a 70year-old woman, and to 25.6% in an 80-year-old woman
(15). The 10-year probability for sustaining any osteoporotic
fracture for a 45-year-old man with a T-score of 22.5 at the
hip is estimated at 6.3% (15). Estimates increase to 9.5% in
a 60-year-old man, to 13.1% in a 70-year-old man, and to
18.7% in an 80-year-old man (15). Similarly, low bone
mass has very different diagnostic and prognostic connotations, depending on a person’s age.
In view of the above, it is clear that the WHO diagnostic classification should not be applied broadly to premenopausal
women or younger men. An additional problem in diagnosing
osteoporosis in women prior to menopause is that reduced
BMD frequently reflects low peak bone mass rather than high
turnover bone loss. Therefore, the pathophysiology is quite different from that seen in postmenopausal osteoporosis. Pharmacologic therapy is rarely indicated in this group based upon
BMD alone.
Can Specific Risk Factors Permit the Use of the
WHO Densitometric Classification in Subgroups
of Premenopausal Women and Younger Men?
In order to address this question, one needs to examine available information regarding fracture risk for a specified BMD in
the presence of specific risk factors. The use of BMD or T-score
as a single predictor of fractures has its limitations, because
there are several powerful predictors of fractures that are
Journal of Clinical Densitometry
Leslie et al.
independent of BMD. Other than age, the strongest risk factors
are prevalent fractures and glucocorticoid therapy (20).
BMD testing may be requested because of the presence of
fragility fracture(s). Premenopausal women and younger men
are at such low risk for non-traumatic fractures, that in the absence of obvious clinical explanation (e.g., solid organ transplant on long-term glucocorticoids), this will normally merit
a thorough evaluation for a diagnosis other than osteoporosis.
Even the finding of unexplained reduced BMD (T-score below 22.5) is not sufficient for diagnosing osteoporosis since
other conditions can also produce reduced BMD and fractures. In such cases, the diagnosis of osteoporosis is based
mostly on the presence of a fragility fracture. The WHO classification is not helpful in quantifying fracture risk or making
a specific diagnosis of osteoporosis in this population.
Long-term glucocorticoid therapy is another independent
predictor of fractures (21). Randomized trials evaluating the
efficacy of various bisphosphonates on preserving BMD
have documented that patients on chronic glucocorticoid therapy tend to fracture at relatively higher BMD (T-score 20.7
to 21.7) (22). Some trials have included men and premenopausal women, although the majority of study participants
were postmenopausal women. In a review by Roux et al
(22), of four separate randomized glucocorticoid trials, the incidence of fracture in premenopausal women on glucocorticoid therapy was 0% (T-score between 20.3 and 20.7)
whereas in men fracture incidence varied between 2–24%
(T-scores between 20.5 and 21.7). Therefore, in these men
on glucocorticoid therapy, but not premenopausal women,
there was evidence of increased fracture risk. The published
data, however, do not indicate which ages of men were at
risk, and how this was modified by the duration and cumulative dose of glucocorticoids. It is not possible, therefore, to
determine the general applicability of the WHO classification
on densitometric diagnostic categories in adult men on glucocorticoids.
In theory, the presence of multiple independent risk factors
for fracture could be used as the basis for applying the WHO
classification. This might exploit flexible fracture risk assessment models, as opposed to rigid T-score thresholds. Such
models could incorporate an individual’s risk profile, including BMD, to estimate individual risk for fracture over a finite
time period (2); however, the influence of many of these risk
factors on fracture risk has not been well characterized in
younger adults (20).
In summary, current data do not support the use of the
WHO diagnostic classification in selected premenopausal
women or younger men, even when there are associated
risk factors other than older age and postmenopausal status.
No clinical risk factors, either singly or in combination,
were identified that would alter this position.
At What Age can the WHO Densitometric
Classification be Applied to Men?
Incident fracture rates in men demonstrate a bimodal distribution (23,24). An early peak in young men (age 20–30
years) that exceeds the fracture rate seen in young women
Volume 9, 2006
Application of the 1994 WHO Classification
is felt to reflect the high rate of traumatic and sports-related
injuries. Very few of these fractures affect the hip or spine,
whereas there is a high rate of craniofacial fracturesda pattern inconsistent with osteoporosis. After approximately age
50–60 years, however, fracture rates in women exceed those
in men, and both show a progressive increase at the fracture
sites that are typical for osteoporotic women. Age-specific
fracture rates in older men are consistently less than in
women, however, with 10-year fracture rates lagging approximately 10–15 years behind those seen in postmenopausal
women (15,24). This creates obvious challenges to diagnosing osteoporosis in young men. Even in middle-aged and
older men, the benefits from targeted BMD testing or screening have not been well studied, therapeutic trials are still limited, and there is a need to better understand the effects and
interactions of clinical risk factors on fracture risk in men.
Despite these differences between men and women, there
are many more similarities. Older age, reduced BMD, low serum-free estradiol, alcohol excess, current smoking, low body
weight, and frailty have each been associated with higher
fracture risk in men and women (21,25–30). The BMD risk
gradient (relative risk per SD) is similar in men and women,
even if their absolute fracture risks differ (31–33); therefore,
the differences between men and women are quantitative, not
qualitative. There is value in having a diagnostic framework
applicable to men and women of the same age so that prevalence of reduced BMD can be derived and compared. Given
the broad acceptance of the WHO diagnostic classification
for postmenopausal women, it is reasonable to apply the
same framework to men starting at age 50, the approximate
age of normal menopause. As noted above, this does not imply a need for testing simply because there is a diagnostic
framework. The alternative position of delaying application
of the WHO classification for men until age 60, 65, or 70
years was discussed but felt to complicate the approach unnecessarily, while restricting the epidemiologic objectives. It
will be recalled from an earlier position in this document
that T-scores (not Z-scores) be used in postmenopausal
women and in men age 50 years or older. This creates a natural connection between the use of T-scores and application of
the WHO densitometric classification while simultaneously
avoiding the latter in premenopausal females and males under
age 50, for whom Z-scores are preferred.
27
secretion (34), possibly related to specific alleles in the variable region of the IGF-I gene (35); low serum levels of free
estradiol (36); and chronic hypercalciuria (37). For these
men, fracture has clinical consequences and treatment is indicated.
What about those men with fracture who do not fit into
the above syndromes? Men who are at risk are those with
defined causes of secondary osteoporosis, most notably glucocorticoid-induced osteoporosis (GIOP). The extant guidelines for GIOP (38) would strongly recommend treatment
for a man aged 50–69 on glucocorticoids, even if the man
has a T-score greater than 22.5. For men with other treatable
causes of osteoporosis, a case can be made to treat the underlying disorder and follow the bone density rather than treat
the T-score. Other disorders that may warrant a bone density
test in a man aged 50–69 would include hypogonadism, malabsorption, alcohol abuse, and hyperparathyroidism (39). In
many cases, the underlying disorder can be treated. For those
men without fracture, amelioration of risk factors (such as vitamin D deficiency, alcohol abuse, etc.) should be undertaken
before starting other specific therapy for osteoporosis. For
those men with fractures, unless there is a specific cause of
osteoporosis amenable to treatment, medication for osteoporosis is indicated.
For men under age 70 without a specific indication, dualenergy X-ray absorptiometry (DXA) testing is not recommended. However, if the patient is tested and has a T score of
22.5 or less, evaluation for secondary causes of osteoporosis
is recommended. For most patients, treatment of underlying
disorders and risk factors plus a repeat DXA in two years
will determine if bone loss is occurring. An unexplained
T-score of 22.5 or less in a man age 50–69 or low trauma
fractures usually warrants evaluation for secondary causes
of osteoporosis.
IV. What Normative Database Should be Used
for Non-White Individuals?
ICSD Official Position
Z-scores should be population specific where adequate
reference data exist. For the purpose of Z-score calculation, the patient’s self-reported ethnicity should be used.
Grade: Poor-C-1
What Is the Clinical Approach to Osteoporosis
by BMD Criteria in a Man Aged 50–69?
Rationale
The management of this situation warrants discussion to
ensure that the clinical approach considers some of the important differences between men and women. The clinical approach to a T-score of –2.5 or lower in a man aged 50–69
must be considered in the context of the clinical presentation.
The usual reason for BMD testing in a man prior to age 70
years is a fracture. A fragility fracture is a risk factor for recurrent fractures, just as in women. There are at least three
clinical syndromes associated with fractures in middle-aged
men: low levels of IGF-I but normal growth hormone
The previous ISCD position was to use a uniform white
(non-race adjusted) female normative database for women
of all ethnic groups, but this statement was limited to the
USA population (5,40). No position was taken with respect
to reference data or ethnicity-matching outside of the USA.
The basis for these recommendations was, in part, based on
the following: (a) defining ethnicity is often difficult, and
(b) multi-ethnic fracture data indicated that the relative risk
(RR) for fracture per SD reduction in peripheral BMD using
a white, young-normal reference population database was
Journal of Clinical Densitometry
Volume 9, 2006
28
similar in five ethnic groups (white, African-Americans,
Asians, Hispanics, and Native Americans) (41).
Discussion
The need for population-specific reference data in order to
calculate T-scores is controversial. In part, this derives from
differences in fracture rates and bone density that had been
observed between countries and different ethnic groups,
with a concern that T-scores derived from a single reference
population may be inappropriate (12,42–45). Developing
and updating young-adult and age-specific reference data
for every combination of country, ethnicity, and gender on every bone density instrument is nearly impossible, and would
challenge the economic resources of most countries while simultaneously creating a veritable Tower of Babel with enormous clinical confusion.
Technical Considerations
The use of population-specific reference data has unique
problems. The major one is that only small differences in
the SD of two different young-normal reference population
databases creates large differences in the calculated T-score
of patients or populations being measured, even when the
same patients are measured on the same DXA manufacturer
(46,47). Hence, the T-score may differ by more than 1.0 SD
in the same patient measured at the same skeletal site on
the same machine, when the T-score is calculated from two
different healthy young-normal reference population databases. Much larger sample sizes are required to reliably estimate the population SD than the population mean peak BMD.
The use of a standardized SD may reduce some of the expected variation that would arise through the use of different
SD values, and is consistent with the principle of a similar
gradient of risk (RR of fracture per SD) in different ethnic
groups, even when absolute fracture rates differ (42).
There are many hurdles to be overcome in the establishment of ethnic-specific reference population databases. One
of these hurdles relates to defining ethnicity. Ethnicity is far
more than just skin color. Ethnicity is a complex interaction
between gene-pool mixes, geography, and socio-cultural factors, and is difficult, if not impossible, to define clinically
(48). Thus, a single racial group can show considerable ethnic
diversity: just as calculating T-scores from two different
white, young-normal reference population databases in the
same postmenopausal white population will yield different
T-scores, so will calculating the T-score from one ethnic,
young-normal reference database and then re-calculating the
T-score using a different ethnically-defined reference database. This can create clinical confusion, especially in nations
where racial diversity is wide, where defining a specific ‘pure’
ethnicity is not easily accomplished, and where there is
significant migration.
Clinical Considerations
An even larger hurdle to making specific reference database recommendations for non-white populations is the paucity of ethnic-specific fracture data, especially lifetime
Journal of Clinical Densitometry
Leslie et al.
fracture risk. Hence, if the same principles whereby the
WHO established their specific cut-points in the white,
post-menopausal population (e.g., linking BMD prevalence
to life-time fracture risk) were to be used in defining densitometric ‘osteoporosis’ in non-white populations, then the same
methodology should be used. This is unlikely to be achieved
in the near future.
Available data suggest that ethnicity-matched reference
data may actually be misleading in terms of fracture risk assessment. Some populations (e.g., African Americans) have
repeatedly been shown to have higher bone density and lower
fracture rates (42,43). Differences in vertebral fracture rates in
European countries are largely explained on the basis of differences in mean BMD and age (45). By contrast, hip fracture
risk in Asians is lower than would be expected from considering BMD alone (42,49,50). Smaller skeletal size and/or differences in hip axis length appear to be a factor in the
paradoxical relationship between BMD and fracture rates in
Asians (51–55). There is evidence that racial size-disparity
is actually diminishing due to secular changes in growth patterns (56,57). The use of a volume-adjusted BMD, such as
bone mineral apparent density (BMAD), might be helpful
in addressing issues related to size as they affect certain ethnic groups and patient populations (58–61). The technique for
calculating BMAD would need to be standardized among
manufacturers and integrated into software so that it could
be easily applied in clinical practice; therefore, it is premature
to develop a position related to BMAD.
Although it would be ideal to have a single reference
database that could be applied globally, there are still some
uncertainties over the global validity of this approach. It
was felt to be premature to alter the existing ISCD position,
which limits the recommendation to use a uniform white
(non-race adjusted) normative database for deriving T-scores
to the USA population. The situation with Z-scores is different since the objective is to compare a patient’s BMD with
a closely matched normal population and not for fracture
prediction (see earlier discussion); therefore, the use of population-specific (i.e., ethnicity-matched) reference data for
deriving Z-scores is a global recommendation.
Where differences in the BMD-fracture relationship are
identified, it cannot be assumed that population-specific reference data will reconcile the difference without direct proof. In
fact, the enormous global variation in fracture risk (lifetime
hip fracture risk for 50-year-old woman from 1% to 28.5%
with 15-fold range in 10-year probability), greatly exceeds
the variation in BMD; therefore, population-specific reference
data will not reconcile all differences in the BMD-fracture relationship. Much more scientific study is needed to define
where differences in fracture rates are (and are not) attributable to population-specific differences in BMD. It is likely
that differences between human populations are smaller
than differences within human populations. Therefore, a single
reference database will probably suffice for most populations.
As noted elsewhere in this issue, NHANES III is a reasonable
standardized platform for hip BMD. Unfortunately, there is
no equivalent for the lumbar spine or forearm. Since the
Volume 9, 2006
Application of the 1994 WHO Classification
WHO absolute fracture risk project relies predominately on
white population studies, it can be validly applied to white
populations (2). Validation of the WHO absolute fracture
risk method in non-white populations will be needed before
this approach can be applied. Population-specific adjustments
may be required where differences in fracture risk are not explained by the risk prediction model developed for white populations.
In Summary
The ISCD Official Positions stated in this paper attempt to
resolve some of the limitations inherent in earlier ISCD Official Positions, as they relate to BMD reporting in groups other
than white (Caucasian), postmenopausal females. While
based on best available evidence, the data to substantiate
the recommendation are incomplete. They will, however,
evolve as the scientific evidence accumulates.
References
1. Report of a WHO Study Group. 1994 Assessment of fracture
risk and its application to screening for postmenopausal osteoporosis. 1994 World Health Organ Tech Rep Ser 843:1–129.
2. Kanis J, Borgstrom F, De Laet C, et al. 2005 Review: assessment
of fracture risk. Osteoporos Int 16:581–589.
3. The Writing Group for the International Society for Clinical
Densitometry (ISCD) Position Development Conference. 2004
Position statement: executive summary. J Clin Densitom 7:7–12.
4. Khan AA, Bachrach L, Brown JP, et al. 2004 Diagnosis of osteoporosis in men, premenopausal women, and children. J Clin
Densitom 7:17–26.
5. Binkley NC, Schmeer P, Wasnich RD, Lenchik L. 2002 What
are the criteria by which a densitometric diagnosis of osteoporosis can be made in males and non-Caucasians? J Clin Densitom
5(Suppl):S19–S27.
6. Leib ES, Lewiecki EM, Binkley N, Hamdy RC. 2004 Official
positions of the International Society for Clinical Densitometry.
J Clin Densitom 7:1–6.
7. Marshall D, Johnell O, Wedel H. 1996 Meta-analysis of how
well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 312:1254–1259.
8. Hodgson SF, Watts NB, Bilezikian JP, et al. 2001 American Association of Clinical Endocrinologists 2001 Medical Guidelines
for Clinical Practice for the Prevention and Management of
Postmenopausal Osteoporosis. Endocr Pract 7:293–312.
9. Stone KL, Seeley DG, Lui LY, et al. 2003 BMD at multiple sites
and risk of fracture of multiple types: long-term results from the
Study of Osteoporotic Fractures. J Bone Miner Res 18:
1947–1954.
10. Ross PD, Davis JW, Epstein RS, Wasnich RD. 1991 Pre-existing
fractures and bone mass predict vertebral fracture incidence in
women. Ann Intern Med 114:919–923.
11. Lu Y, Genant HK, Shepherd J, et al. 2001 Classification of osteoporosis based on bone mineral densities. J Bone Miner Res 16:
901–910.
12. Looker AC, Wahner HW, Dunn WL, et al. 1998 Updated data on
proximal femur bone mineral levels of US adults. Osteoporos Int
8:468–489.
13. Cummings SR, Nevitt MC, Browner WS, et al. Study of Osteoporotic Fractures Research Group. 1995 Risk factors for hip
fracture in white women. N Engl J Med 332:767–773.
Journal of Clinical Densitometry
29
14. Espallargues M, Sampietro-Colom L, Estrada MD, et al. 2001
Identifying bone-mass-related risk factors for fracture to guide
bone densitometry measurements: a systematic review of the literature. Osteoporos Int 12:811–822.
15. Kanis JA, Johnell O, Oden A, Dawson A, De Laet C, Jonsson B.
2001 Ten year probabilities of osteoporotic fractures according
to BMD and diagnostic thresholds. Osteoporos Int 12:989–995.
16. Hui SL, Slemenda CW, Johnston CC Jr. 1988 Age and bone
mass as predictors of fracture in a prospective study. J Clin
Invest 81:1804–1809.
17. Fuleihan G, Baddoura R, Awada H, Okais J, Rizk P,
McClung M. 2005 Lebanese guidelines for osteoporosis assessment and treatment: Who to test? What measures to use? When
to treat? J Clin Densitom 8:148–163.
18. Kelepouris N, Harper KD, Gannon F, Kaplan FS, Haddad JG.
1995 Severe osteoporosis in men. Ann Intern Med 123:
452–460.
19. Selby PL, Davies M, Adams JE. 2000 Do men and women fracture bones at similar bone densities? Osteoporos Int 11:153–157.
20. Kanis JA, Gluer CC, Committee of Scientific Advisors, International Osteoporosis Foundation. 2000 An update on the diagnosis and assessment of osteoporosis with densitometry.
Osteoporos Int 11:192–202.
21. Kanis JA, Johansson H, Oden A, et al. 2004 A meta-analysis of
prior corticosteroid use and fracture risk. J Bone Miner Res 19:
893–899.
22. Roux C, Orcel P. 2003 Steroid induced osteoporosis: prevention
and treatment. Rev Med Interne 24:384–388.
23. Leslie WD, Derksen S, Metge C, et al. 2004 Fracture risk among
First Nations people: a retrospective matched cohort study.
CMAJ 171:869–873.
24. Singer BR, McLauchlan GJ, Robinson CM, Christie J. 1998 Epidemiology of fractures in 15,000 adults: the influence of age
and gender. J Bone Joint Surg Br 80:243–248.
25. Binkley N, Krueger D. 2002 Osteoporosis in men. WMJ 101:
28–32.
26. Kanis JA, Johansson H, Johnell O, et al. 2005 Alcohol intake as
a risk factor for fracture. Osteoporos Int 16:737–742.
27. Olszynski WP, Shawn DK, Adachi JD, et al. 2004 Osteoporosis
in men: epidemiology, diagnosis, prevention, and treatment. Clin
Ther 26:15–28.
28. Orwoll ES. 2003 Men, bone and estrogen: unresolved issues. Osteoporos Int 14:93–98.
29. Olofsson H, Byberg L, Mohsen R, Melhus H, Lithell H,
Michaelsson K. 2005 Smoking and the risk of fracture in older
men. J Bone Miner Res 20:1208–1215.
30. Kanis JA, Johnell O, Oden A, et al. 2005 Smoking and fracture
risk: a meta-analysis. Osteoporos Int 16:155–162.
31. Kanis JA, Johnell O, Oden A, De Laet C, Mellstrom D. 2001 Diagnosis of osteoporosis and fracture threshold in men. Calcif
Tissue Int 69:218–221.
32. De Laet CE, Van Hout BA, Burger H, Weel AE, Hofman A,
Pols HA. 1998 Hip fracture prediction in elderly men and
women: validation in the Rotterdam study. J Bone Miner Res
13:1587–1593.
33. van der KM, De Laet CE, McCloskey EV, Hofman A, Pols HA.
2002 The incidence of vertebral fractures in men and women:
the Rotterdam Study. J Bone Miner Res 17:1051–1056.
34. Kurland ES, Rosen CJ, Cosman F, et al. 1997 Insulin-like growth
factor-I in men with idiopathic osteoporosis. J Clin Endocrinol
Metab 82:2799–2805.
35. Rosen CJ, Kurland ES, Vereault D, et al. 1998 Association between serum insulin growth factor-I (IGF-I) and a simple sequence repeat in IGF-I gene: implications for genetic studies
of bone mineral density. J Clin Endocrinol Metab 83:2286–2290.
Volume 9, 2006
30
36. Van Pottelbergh I, Goemaere S, Zmierczak H, Kaufman JM.
2004 Perturbed sex steroid status in men with idiopathic osteoporosis and their sons. J Clin Endocrinol Metab 89:
4949–4953.
37. Zerwekh JE, Sakhaee K, Breslau NA, Gottschalk F, Pak CY.
1992 Impaired bone formation in male idiopathic osteoporosis:
further reduction in the presence of concomitant hypercalciuria.
Osteoporos Int 2:128–134.
38. Lippuner K, Golder M, Greiner R. 2005 Epidemiology and
direct medical costs of osteoporotic fractures in men and women
in Switzerland. Osteoporos Int 16(Suppl 2):S8–S17.
39. Bilezikian JP. 1999 Osteoporosis in men. J Clin Endocrinol
Metab 84:3431–3434.
40. Lenchik L, Leib ES, Hamdy RC, Binkley NC, Miller PD,
Watts NB. 2002 Executive summary International Society for
Clinical Densitometry position development conference Denver,
Colorado July 20–22, 2001. J Clin Densitom 5(Suppl):S1–S3.
41. Miller PD, Siris ES, Barrett-Connor E, et al. 2002 Prediction of
fracture risk in postmenopausal white women with peripheral
bone densitometry: evidence from the National Osteoporosis
Risk Assessment. J Bone Miner Res 17:2222–2230.
42. Barrett-Connor E, Siris ES, Wehren LE, et al. 2005 Osteoporosis
and fracture risk in women of different ethnic groups. J Bone
Miner Res 20:185–194.
43. Cauley JA, Lui LY, Ensrud KE, et al. 2005 Bone mineral density
and the risk of incident nonspinal fractures in black and white
women. JAMA 293:2102–2108.
44. Kanis JA, Johnell O, De Laet C, Jonsson B, Oden A,
Ogelsby AK. 2002 International variations in hip fracture probabilities: implications for risk assessment. J Bone Miner Res 17:
1237–1244.
45. Lunt M, Felsenberg D, Reeve J, et al. 1997 Bone density variation and its effects on risk of vertebral deformity in men and
women studied in thirteen European centers: the EVOS Study.
J Bone Miner Res 12:1883–1894.
46. Binkley N, Kiebzak GM, Lewiecki EM, et al. 2005 Recalculation of the NHANES Database SD Improves T-Score Agreement
and Reduces Osteoporosis Prevalence. J Bone Miner Res 20:
195–201.
47. Leslie WD, Caetano PA, Roe EB. 2005 The impact of hip subregion reference data on osteoporosis diagnosis. Osteoporos Int
16:1669–1674.
48. Cooper R. 2002 A note on the biological concept of race and its
application in epidemiologic research. LaVeist TA, ed. Race,
ethnicity and health: a public health reader. San Francisco: Jossey-Bass, 99–114.
Journal of Clinical Densitometry
Leslie et al.
49. Ross PD, Norimatsu H, Davis JW, et al. 1991 A comparison of
hip fracture incidence among native Japanese, Japanese Americans, and American Caucasians. Am J Epidemiol 133:801–809.
50. Lau EM, Lee JK, Suriwongpaisal P, et al. 2001 The incidence of
hip fracture in four Asian countries: the Asian Osteoporosis
Study (AOS). Osteoporos Int 12:239–243.
51. Ross PD, He Y, Yates AJ, et al. The EPIC (Early Postmenopausal Interventional Cohort) Study Group. 1996 Body size accounts for most differences in bone density between Asian and
Caucasian women. Calcif Tissue Int 59:339–343.
52. Bhudhikanok GS, Wang MC, Eckert K, Matkin C, Marcus R,
Bachrach LK. 1996 Differences in bone mineral in young Asian
and Caucasian Americans may reflect differences in bone size.
J Bone Miner Res 11:1545–1556.
53. Cummings SR, Cauley JA, Palermo L, et al. Study of Osteoporotic Fractures Research Group. 1994 Racial differences in hip
axis lengths might explain racial differences in rates of hip fracture. Osteoporos Int 4:226–229.
54. Chin K, Evans MC, Cornish J, Cundy T, Reid IR. 1997 Differences in hip axis and femoral neck length in premenopausal
women of Polynesian, Asian and European origin. Osteoporos
Int 7:344–347.
55. Wang MC, Aguirre M, Bhudhikanok GS, et al. 1997 Bone mass
and hip axis length in healthy Asian, black, Hispanic, and white
American youths. J Bone Miner Res 12:1922–1935.
56. Tanner JM, Hayashi T, Preece MA, Cameron N. 1982 Increase
in length of leg relative to trunk in Japanese children and adults
from 1957 to 1977: comparison with British and with Japanese
Americans. Ann Hum Biol 9:411–423.
57. Hauspie RC, Vercauteren M, Susanne C. 1997 Secular changes
in growth and maturation: an update. Acta Paediatr Suppl 423:
20–27.
58. Benbassat CA, Eshed V, Kamjin M, Laron Z. 2003 Are adult patients with Laron syndrome osteopenic? A comparison between
dual-energy X-ray absorptiometry and volumetric bone densities. J Clin Endocrinol Metab 88:4586–4589.
59. Jergas M, Breitenseher M, Gluer CC, Yu W, Genant HK. 1995
Estimates of volumetric bone density from projectional measurements improve the discriminatory capability of dual X-ray
absorptiometry. J Bone Miner Res 10:1101–1110.
60. Neely EK, Marcus R, Rosenfeld RG, Bachrach LK. 1993 Turner
syndrome adolescents receiving growth hormone are not osteopenic. J Clin Endocrinol Metab 76:861–866.
61. Carter DR, Bouxsein ML, Marcus R. 1992 New approaches for
interpreting projected bone densitometry data. J Bone Miner Res
7:137–145.
Volume 9, 2006