The Canadian SCORE questionnaire: optimizing the use of technology for low bone density assessment. Simple Calculated Osteoporosis Risk Estimate

Current status and dilemmas of osteoporosis screening tools: A narrative review

OBJECTIVE

This review aims to explore the strengths and dilemmas of existing osteoporosis screening tools and suggest possible ways of optimization, in addition to exploring the potential of AI-integrated X-ray imaging in osteoporosis screening, especially its ability to improve accuracy and applicability to different populations. To break through the dilemma of low accessibility, poor clinical translation, complexity of use, and apparent limitations of screening results of existing osteoporosis screening tools.

DATA SOURCES

A comprehensive literature search was performed using PubMed, Web of Science, and CNKI databases. The search included articles published between 2000 and 2023, focusing on studies evaluating osteoporosis screening tools, Artificial intelligence applications in medical imaging, and implementing AI technologies in clinical settings.

STUDY SELECTION

The Osteoporosis Risk Assessment Tool for Asians (OSTA), the Simple Calculated Osteoporosis Risk Estimator (SCORE), age, body size, one or no estrogen ever (ABONE), and the Osteoporosis Risk Index (OSIRIS) are the six commonly used screening tools for osteoporosis that are discussed in this review. In addition, the performance of AI-integrated imaging systems is explored in light of relevant research advances in Artificial intelligence in osteoporosis screening. Studies of the use of these tools in different populations and their advantages and disadvantages were included in the selection criteria.

RESULTS

The results highlight that AI-integrated X-ray imaging technologies offer significant improvements over traditional osteoporosis screening tools. Artificial intelligence systems demonstrated higher accuracy by incorporating complex clinical data and providing personalized assessments for diverse populations. The studies showed that AI-driven imaging could enhance sensitivity and specificity, particularly in detecting early-stage bone density loss in patients with complex clinical profiles. The findings also suggest that Artificial intelligence technologies have the potential to be effectively applied in resource-limited settings through the use of mobile devices and remote diagnostics.

CONCLUSIONS

AI-integrated X-ray imaging technology significantly advances osteoporosis screening, offering more accurate and adaptable solutions than traditional tools. Its ability to incorporate complex clinical data and apply it across various demographic groups makes it particularly promising in diverse and resource-limited environments. Further research is needed to explore the full potential of AI in enhancing screening accessibility and effectiveness, particularly in underserved populations.

Screening for Osteoporosis Risk Among Community-Dwelling Older Adults: A Scoping Review

BACKGROUND AND PURPOSE

Due to potential health-related consequences of osteoporosis (OP), health care providers who do not order imaging, such as physical therapists, should be aware of OP screening tools that identify individuals who need medical and rehabilitation care. However, current knowledge and guidance on screening tools is limited. Therefore, we explored OP screening tools that are appropriate and feasible for physical therapy practice, and evaluated tools' effectiveness by examining their clinimetric properties.

METHODS

A systematic search of the following databases was performed: PubMed, PEDro, PsycINFO, CINAHL, and Web of Science. Articles were included if the study population was 50 years and older, had a diagnosis of OP, if the screening tool was within the scope of physical therapy practice, and was compared to either a known diagnosis of OP or bone densitometry scan results. Included articles underwent multiple reviews for inclusion and exclusion, with each review round having a different randomly selected pair of reviewers. Data were extracted from included articles for participant demographics, outcome measures, cut-off values, and clinimetric properties. Results were categorized with positive and negative likelihood ratios (+LR/-LR) based on the magnitude of change in the probability of having or not having OP.

RESULTS

+LRs ranged from 0.15 to 20.21, with the Fracture Risk Assessment Tool (FRAX) and Study of Osteoporotic Fractures (SOF) having a large shift in posttest probability. -LRs ranged from 0.03 to 1.00, with the FRAX, Male Osteoporosis Risk Estimation Scores, Osteoporosis Self-Assessment Tool (OST), and Simple Calculated Osteoporosis Risk Estimation having a large shift in posttest probability.

CONCLUSION

Tools with moderate-large shift for both +LR and -LR recommended for use are: (1) OST; (2) FRAX; and (3) SOF. The variability in cut-off scores and clinimetric properties based on gender, age, and race/ethnicities made it impossible to provide one specific recommendation for an OP screening tool. Future research should focus on OP risk prediction among males and racial and ethnic groups.

Risk Assessment Tools for Osteoporosis Screening in Postmenopausal Women: A Systematic Review

Osteoporotic fractures are common in postmenopausal women. Tools are available to estimate the risk of low bone mineral density (BMD) or fracture. This systematic review retrieved articles that evaluated osteoporosis risk assessment tools among postmenopausal women in North America. For identifying BMD T-score ≤-2.5, most studies of the Simple Calculated Osteoporosis Risk Estimation tool (SCORE) and Osteoporosis Risk Assessment Instrument (ORAI) reported sensitivity ≥90 %. Area under the receiver operating characteristic curve (AUC) was usually <0.75 for SCORE and ≥0.75 for ORAI. Among women 50-64 years old, a Fracture Risk Assessment Tool (FRAX) threshold ≥9.3 % had a sensitivity of 33 % for identifying BMD T-score ≤-2.5 and 26 % for predicting major osteoporotic fracture (MOF). For predicting MOF, sensitivity was higher for SCORE and Osteoporosis Self-assessment Tool equation (OST), and higher in women ≥65 years old. For predicting BMD T-score ≤-2.5 in women ≥65 years old, the sensitivities of SCORE; ORAI; and Age, Body Size, No Estrogen (ABONE) were very high. No optimal osteoporosis risk assessment tool is available for identifying low BMD and MOF risk.

Diagnostic thresholds in osteoporosis: how are they used in clinical trials?

Clinical trials are used to determine the efficacy and safety of a medication prior to approval for commercial use and to influence the prescribing habits of clinicians. The lack of uniformity in the diagnostic thresholds used in clinical trials on osteoporosis makes it difficult to compare the results of these trials. The use of placebo, different anatomical sites, T-score cutoff points, and risk factors precludes any meaningful comparison being made between the outcomes of clinical trials. Finally, the lack of uniform reporting format makes it difficult to retrieve important information to compare one medication to another. Because the diagnostic thresholds used affect the outcomes of these trials, health care providers need to be aware of these criteria to determine whether the results of a particular clinical trial can be applied to a particular patient.

Nutrition as a Determinant of Successful Aging: Description of the Quebec Longitudinal Study NuAge and Results from Cross-Sectional Pilot Studies

Optimal nutrition is essential for general well being, maintenance of physical and functional capacities and prevention of chronic disease in the elderly. The 5-year longitudinal study, NuAge, was designed to assess the pivotal role of nutrition on physical and cognitive status, functional autonomy and social functioning. A cohort of 1793 men and women, selected from three age groups (68-72, 73-77, 78-82) at recruitment, has been followed annually since 2003-2004. A plurimethodological approach, including basic, clinical, epidemiologic, and social research has been used. Data on various facets of nutritional status (diet, food habits, appetite, anthropometry and body composition), and functional (muscle strength, physical activity, physical and functional capacities and performance), medical (physical, mental and cognitive health, medication) and social data (network, support, participation) are collected by questionnaires or direct measurements. Blood, urine, and saliva samples are also collected and processed for genomic, transcriptomic, proteomic, and biochemical analyses and to study markers of endocrine, immune, and cognitive functions. Selected bio-psycho-social characteristics of the cohort, consumption of macronutrients, and biologic variables are presented, including the impact of intake of certain foods on total antioxidant status. Understanding the aging process as regulated by a modifiable factor such as nutrition should facilitate the development of targeted strategies for promoting successful aging.

Which screening strategy using BMD measurements would be most cost effective for hip fracture prevention in elderly women? A decision analysis based on a Markov model

INTRODUCTION

Hip fractures are responsible for excessive mortality, decreasing the 5-year survival rate by about 20%. From an economic perspective, they represent a major source of expense, with direct costs in hospitalization, rehabilitation, and institutionalization. The incidence rate sharply increases after the age of 70, but it can be reduced in women aged 70-80 years by therapeutic interventions. Recent analyses suggest that the most efficient strategy is to implement such interventions in women at the age of 70 years. As several guidelines recommend bone mineral density (BMD) screening of postmenopausal women with clinical risk factors, our objective was to assess the cost-effectiveness of two screening strategies applied to elderly women aged 70 years and older.

METHODS

A cost-effectiveness analysis was performed using decision-tree analysis and a Markov model. Two alternative strategies, one measuring BMD of all women, and one measuring BMD only of those having at least one risk factor, were compared with the reference strategy "no screening". Cost-effectiveness ratios were measured as cost per year gained without hip fracture. Most probabilities were based on data observed in EPIDOS, SEMOF and OFELY cohorts.

RESULTS

In this model, which is mostly based on observed data, the strategy "screen all" was more cost effective than "screen women at risk." For one woman screened at the age of 70 and followed for 10 years, the incremental (additional) cost-effectiveness ratio of these two strategies compared with the reference was 4,235 euros and 8,290 euros, respectively.

CONCLUSION

The results of this model, under the assumptions described in the paper, suggest that in women aged 70-80 years, screening all women with dual-energy X-ray absorptiometry (DXA) would be more effective than no screening or screening only women with at least one risk factor. Cost-effectiveness studies based on decision-analysis trees maybe useful tools for helping decision makers, and further models based on different assumptions should be performed to improve the level of evidence on cost-effectiveness ratios of the usual screening strategies for osteoporosis.

Canadian Consensus Conference on osteoporosis, 2006 update

OBJECTIVE

To provide guidelines for the health care provider on the diagnosis and clinical management of postmenopausal osteoporosis.

OUTCOMES

Strategies for identifying and evaluating high-risk individuals, the use of bone mineral density (BMD) and bone turnover markers in assessing diagnosis and response to management, and recommendations regarding nutrition, physical activity, and the selection of pharmacologic therapy to prevent and manage osteoporosis.

EVIDENCE

MEDLINE and the Cochrane database were searched for articles in English on subjects related to osteoporosis diagnosis, prevention, and management from March 2001 to April 2005. The authors critically reviewed the evidence and developed the recommendations according to the Journal of Obstetrics and Gynaecology Canada's methodology and consensus development process.

VALUES

The quality of evidence is rated using the criteria described in the report of the Canadian Task Force on the Periodic Health Examination. Recommendations for practice are ranked according to the method described in this report.

SPONSORS

The development of this consensus guideline was supported by unrestricted educational grants from Berlex Canada Inc., Lilly Canada, Merck Frosst, Novartis, Novogen, Novo Nordisk, Proctor and Gamble, Schering Canada, and Wyeth Canada.

Comparison of questionnaire and quantitative ultrasound techniques as screening tools for DXA

The aim of the study is to assess the sensitivity and specificity of different techniques and their ability to act as screening tools in relation to dual energy X-ray absorptiometry (DXA) in a group of 208 postmenopausal women. In this study we examined eight screening systems for the diagnosis of osteoporosis, the osteoporosis self-assessment tool (OST), the osteoporosis risk assessment instrument (ORAI), the osteoporosis index of risk (OSIRIS), a risk index derived using data from the study of osteoporotic fractures (SOFSURF), the simple calculated osteoporosis risk estimation (SCORE), patient body weight (pBW), along with two ultrasound based systems, the Sunlight Omnisense (Sunlight Medical, Rehovot, Israel) and the CUBA Clinical (McCue plc, Winchester, UK). The sensitivity and specificity of the different techniques in relation to DXA were plotted as receiver-operating characteristic (ROC) curves at three different levels (DXA T-score -2.5 osteoporosis, -2 and -1 osteopenia). The areas under the curves (AUC) were calculated and showed broadband ultrasound attenuation (BUA) at the calcaneus to provide consistently the highest AUC (0.77-0.81). The velocity of sound (VOS) of the calcaneus (AUC=0.72-0.76) was equally good, but was out-performed by some of the questionnaire systems (AUC=0.66-0.79). Both the questionnaire systems and the CUBA Clinical out-perform the Sunlight Omnisense (AUC=0.58-0.7), which showed comparable performance with body weight (AUC=0.66-0.69). The results show that QUS is capable of selecting patients with low bone density as measured by DXA. A patient displaying a low QUS value should be followed up with a DXA scan to confirm the diagnosis.

Osteoporosis case finding in the general practice: phalangeal radiographic absorptiometry with and without risk factors for osteoporosis to select postmenopausal women eligible for lumbar spine and hip densitometry

Mass screening for osteoporosis using DXA measurements at the spine and hip is presently not recommended by health authorities. Instead, risk factor questionnaires and peripheral bone measurements may facilitate the selection of women eligible for axial bone densitometry. The aim of this study was to validate a case finding strategy for postmenopausal women who would benefit most from subsequent DXA measurement by using phalangeal radiographic absorptiometry (RA) alone or in combination with risk factors in a general practice setting. The sensitivity and specificity of this strategy in detecting osteoporosis (T-score < or =2.5 SD at the spine and/or the hip) were compared with those of the current reimbursement criteria for DXA measurements in Switzerland. Four hundred and twenty-three postmenopausal women with one or more risk factors for osteoporosis were recruited by 90 primary care physicians who also performed the phalangeal RA measurements. All women underwent subsequent DXA measurement of the spine and the hip at the Osteoporosis Policlinic of the University Hospital of Berne. They were allocated to one of two groups depending on whether they matched with the Swiss reimbursement conditions for DXA measurement or not. Logistic regression models were used to predict the likelihood of osteoporosis versus "no osteoporosis" and to derive ROC curves for the various strategies. Differences in the areas under the ROC curves (AUC) were tested for significance. In women lacking reimbursement criteria, RA achieved a significantly larger AUC (0.81; 95% CI 0.72-0.89) than the risk factors associated with patients' age, height and weight (0.71; 95% C.I. 0.62-0.80). Furthermore, in this study, RA provided a better sensitivity and specificity in identifying women with underlying osteoporosis than the currently accepted criteria for reimbursement of DXA measurement. In the Swiss environment, RA is a valid case finding tool for patients with risk factors for osteoporosis, especially for those who do not qualify for DXA reimbursement.

Performance of four clinical screening tools to select peri- and early postmenopausal women for dual X-ray absorptiometry

Several methods to select postmenopausal women for dual X-ray absorptiometry (DXA) have been proposed. We decided to compare the performance of three clinical decision rules (SCORE, ORAI, OST) with the usual case-finding strategy based on the presence of a major risk factor for future fracture (CFMRF). The study subjects were 2009 healthy, white, peri- or early postmenopausal women participating in the Danish Osteoporosis Prevention Study (DOPS). DXA results expressed as T-scores and scores on SCORE, ORAI, OST and CFMRF were extracted from the DOPS database. First, we evaluated the screening tools as originally described by the developers. The resulting sensitivities and specificities ranged from 18% to 92% and from 66% to 85%, respectively. Only OST achieved a high sensitivity (92%) with respect to femoral neck T-score < or = -2.5; however, the sensitivity with respect to lumbar spine T-score < or = -2.5 was only 51%. Next, the performance of the screening tools was evaluated against T-score < or = -2.0 (and T-score < or = -2.5) in at least one of the regions: femoral neck, total hip or lumbar spine. Using ROC curve analysis, we determined cut-offs yielding sensitivities as close as possible to 90%. The CFMRF and the ORAI tool were too coarse to yield 90% sensitivity. The performances of OST and SCORE were equal from a clinical perspective in that the sensitivities and the specificities varied from 89% to 94% and from 23% to 28%, respectively. The performance of CFMRF was no better than could be expected by chance, yielding a sensitivity of 19% and a specificity of 85%. Applying SCORE or OST 75% of the women would have to be referred for densitometry to identify 90% of the women with T-score < or = -2.0 (or T-score < or = -2.5) in at least one region. In conclusion, our results question the utility of all the evaluated tools for screening peri- and early postmenopausal women for low BMD. However, if a decision on referral has to be made, it may be based on the simple OST rule, which performed as well as or better than any of the other tools.

Usefulness of the SCORE Index as a Predictor of Osteoporosis in Women With Disabilities

BACKGROUND

Osteoporosis is widely recognized as a common health problem among older women. It has also recently been identified as common in both pre- and postmenopausal women with disabilities. Although several clinical indices have been developed to identify nondisabled women likely to have low bone mineral density (BMD) when tested, studies that have tested the usefulness of these clinical indices have excluded women with disabilities. Thus, the usefulness of these indices in predicting low BMD and osteoporosis in women with disabilities is unknown.

PURPOSE

This study examined the ability of one of these indices, the Simple Calculated Osteoporosis Risk Estimation (SCORE), to identify women with disabilities likely to have low BMD on screening. SAMPLE/DATA COLLECTION: Women with disabilities (N = 307) responded to the six-item SCORE index and underwent peripheral BMD screening. The sensitivity, specificity, and accuracy of the SCORE index in predicting BMD with the criterion of a T-score of </=2.5 were 65.7, 61.1, and 62.2%, respectively. When a T-score of </=2.0 was used as the criterion, the sensitivity, specificity, and accuracy of the SCORE index were 62.6, 63, and 62.9%, respectively.

FINDINGS

The low sensitivity, specificity, and accuracy of the SCORE index indicate that it is not a useful predictor of low BMD in women with disabilities, incorrectly categorizing almost 40% of the sample. A clinical index that includes osteoporosis risk factors present in women with disabilities is needed to increase the likelihood that women with disabilities will be referred for testing and receive treatment of osteoporosis when indicated.

Development and validation of the osteoporosis prescreening risk assessment (OPERA) tool to facilitate identification of women likely to have low bone density

Osteoporosis and its consequent increase in fracture risk is a major health concern for postmenopausal women and older men and has the potential to reach epidemic proportions. The "gold standard" for osteoporosis diagnosis is bone densitometry. However, economic issues or availability of the technology may prevent the possibility of mass screening. The goal of this study was to develop and validate a clinical scoring index designed as a prescreening tool to help clinicians identify which women are at increased risk of osteoporosis [bone mineral density (BMD) T-score -2.5 or less] and should therefore undergo further testing with bone densitometry. Records were analyzed for 1522 postmenopausal females over 50 years of age who had undergone testing with dual-energy X-ray absorptiometry (DXA). Osteoporosis risk index scores were compared to bone density T-scores. Hologic QDR 4500 technology was used to measure BMD at the femoral neck and lumbar spine (L1-L4). Participants who had a previous diagnosis of osteoporosis or were taking bone-active medication were excluded. Receiver-operating characteristic (ROC) analysis was used to identify the specific cutpoint value that would identify women at increased risk of low BMD. A simple algorithm based on age, weight, history of previous low impact fracture, early menopause, and corticosteroid therapy was developed. Validation of this five-item osteoporosis prescreening risk assessment (OPERA) index showed that the tool, at the recommended threshold (or cutoff value) of two, had a sensitivity that ranged from 88.1 [95% confidence interval (CI) for the mean: 86.2-91.9%] at the femoral neck to 90% (95% CI for the mean: 86.1-93.1%) at the lumbar spine area. Corresponding specificity values were 60.6 (95% CI for the mean: 57.9-63.3%) and 64.2% (95% CI for the mean: 61.4-66.9%), respectively. The positive predictive value (PPV) ranged from 29 at the femoral neck to 39.2% at the lumbar spine, while the corresponding negative predictive values (NPVs) reached 96.5 and 96.2%, respectively. Based on this cutoff value, the area under the ROC curve was 0.866 (95% CI for the mean: 0.847-0.882) for the lumbar spine and 0.814 (95% CI for the mean: 0.793-0.833) for the femoral neck. We conclude that the OPERA is a free and effective method for identifying Italian postmenopausal women at increased risk of osteoporosis. Its use could facilitate the appropriate and more cost-effective use of bone densitometry in developing countries.

Beyond bone mineral density: can existing clinical risk assessment instruments identify women at increased risk of osteoporosis?

OBJECTIVE

Although osteoporosis and fragility fracture are common amongst postmenopausal women, the extent of risk varies, and measurement of bone mineral density (BMD) is the standard tool used to diagnose and assess fracture risk. Rates of diagnosis remain relatively low, and several groups have developed instruments to help identify individuals who would most benefit from BMD testing. In this paper, we review and compare the performance of these instruments to identify those most useful in the primary care setting.

DESIGN

Review of screening instruments comprised osteoporosis clinical risk factors and comparison of the sensitivity and specificity of these algorithms.

RESULTS

Validated instruments have varying complexity, but similar sensitivity and specificity for identifying individuals who are likely to have low BMD. The area under the receiver operating characteristic curve ranges from 0.75 (SOFSURF) to 0.81 (SCORE). The simplest of the instruments (OST) uses only age and weight and has an AUC of 0.79.

CONCLUSIONS

The Osteoporosis Self-assessment Tool, the simplest of the instruments, performs as well as more complex tools and, because of its simplicity, may be the most useful means for the busy clinician to identify postmenopausal women who would most benefit from BMD testing.

Evaluation of an osteoporosis self-referral program to enhance management outcomes

Osteoporosis is a common but undertreated condition. While bone density is known to predict fracture risk, there is currently no economical way of measuring general population risk. This study examined whether an economical screening technique could improve diagnosis and lead to appropriate outcomes in the management of osteoporosis. A self-referral program was established to provide women with information about osteoporosis and an individualized risk assignment. A high-risk designation was provided for postmenopausal women below the lower tertile of a calcaneal broadband ultrasound attenuation (BUA) (< or = 58 db/MHz) or those with a SCORE value > or = 6. A telephone survey was conducted 6 mo after program registration to evaluate osteoporosis management outcomes. Of 271 women surveyed, 181 (67%) were postmenopausal and thus potential candidates for estrogen replacement, and 21% and 63% were assigned a high-risk profile by either calcaneal ultrasound or SCORE, respectively. Women at higher risk were significantly more likely to discuss osteoporosis with their family physician (p < 0.001), and to undergo further testing with dual X-ray absorptiometry measurement (p < 0.005). Utilization of estrogen replacement by postmenopausal women at time of survey was significantly increased compared to registration (p = 0.01). The self-referral program positively impacted decisions women made about preventing osteoporosis, particularly if they considered themselves at higher risk.

Further validation of a questionnaire to identify women likely to have low bone density

A questionnaire instrument called the Simple Calculated Osteoporosis Risk Estimation (SCORE*) stratifies risk for osteoporosis, potentially reducing population-screening costs. SCORE is calculated using race, weight, age, history of estrogen use, fracture history, and presence/absence of rheumatoid arthritis. We tested SCORE in 912 postmenopausal women aged 45 yr or more using a Hologic QDR4500C densitometer for the total hip, femoral neck, and lumbar spine. National Health and Nutrition Examination Survey (NHANES III) norms were used to calculate hip T-scores. Low bone density (T-score < -2.0) was found in 29.6% of patients at the femoral neck, 17.7% at the total hip, 36.1% at the lumbar spine, and 46.1% at one or more sites. The sensitivity/specificity of the SCORE model (using a threshold of 6 points) was 0.97/0.36 for the femoral neck, 0.95/0.30 for the total hip, 0.86/0.35 for the spine, and 0.88/0.41 for any site (total hip, femoral neck, or spine). When used to detect low bone density at any site, SCORE would have deferred 27.6% of women referred for DXA scans, but 20.7% of these (5.7% of the entire population) would have been false-negatives, and thus inappropriately deferred. At a cutpoint of 3 instead of 6, sensitivity/specificity was 0.96/0.16. In those aged 50-60, the group with the greatest need for risk stratification, sensitivity/specificity for low density at any site was 0.72/0.54, and 46.1% would have been deferred, but 18.5% of this group would have been false-negatives. A cutpoint of 1 in this age group yielded sensitivity/specificity of 0.94/0.16. After age 65, few women would be deferred.

CONCLUSION

When used to detect low bone density at any site with sufficient sensitivity for clinical practice, SCORE did not have sufficient discriminatory power to be broadly applicable.

Performance of risk indices for identifying low bone density in postmenopausal women

OBJECTIVE

To examine the ability of 4 published osteoporosis risk indices to identify women with low bone density.

SUBJECTS AND METHODS

Subjects included postmenopausal women 45 years and older consecutively recruited from US clinics, women from general practice centers in The Netherlands (age range, 50-80 years), women in the Rotterdam Study (The Netherlands) 55 years and older, and women aged 55 to 81 years old screened for a clinical trial of alendronate. Bone mineral density (BMD) was measured at the femoral neck or lumbar spine; T scores represent the number of SDs below the mean for young healthy women. One risk index was calculated from age and weight; the other risk indices included up to 4 additional variables obtained by questionnaire. We calculated the sensitivity and specificity for identifying women with BMD T scores of -2.5 or less or -2.0 or less in the US clinic sample and created 3 risk categories, using each of the 4 indices.

RESULTS

Data were available for 1102 women from the US clinic sample, 3374 women in the Rotterdam Study, 23,833 women screened for a clinical trial of alendronate, and 4204 women from general practice centers in The Netherlands. Specificity for identifying BMD T scores of -2.5 or less ranged from 37% to 58% (depending on risk index) when sensitivity was approximately 90%. The prevalence of osteoporosis (defined as T scores < or = -2.5) differed widely across the 3 risk categories, ranging from 2% to 4% for the low-risk category to 47% to 61% for the high-risk category in the US clinic sample. For spine BMD in the US clinic sample, the prevalence of T scores of -2.5 or less ranged from 7% (low risk) to 38% (high risk). The large differences in prevalence across risk categories were consistent across the other 3 samples of postmenopausal women in the United States and The Netherlands for all 4 risk indices.

CONCLUSIONS

We recommend measuring BMD in women who are classified as having an increased risk of osteoporosis by using any of these risk indices because all 4 indices appear to predict low bone mass equally well. The Osteoporosis Self-assessment Tool index is easiest to calculate and therefore may be most useful in clinical practice.