Limited Clinical Utility of a Self-Evaluating Risk Assessment Scale for Postmenopausal Osteoporosis: Lack of Predictive Value of Lifestyle-Related Factors

Goemaere, Stefan; Zegels, Brigitte; Toye, Kaatje; Cremer, Steven A.; Demuynck, Rein; Daems, M; Dobbelaere, K; Sedrine, Wafa Ben; Albert, Adelin; Dewé, Walthère; Kaufman, Jean; Reginster, JY

doi:10.1007/s002239900712

Cited by 14 publications

(7 citation statements)

References 20 publications

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“…37 These findings are consistent with earlier studies of white and Asian women that reported that age and weight were important predictors of BMD, and that indices based on age and weight performed as well as models that included additional variables. [18][19][20][21][22]35,38 In fact, the algorithm for calculating OsteoRisk risk for osteoporosis developed in the current study is exactly the same as the algorithm developed independently for the OST and the OSTA, which was originally developed in an Asian cohort and later validated in white cohorts. [18][19][20]35 The OsteoRisk cutoffs for defining high, medium, and low risk are slightly different from those reported for the OST, which may in part reflect ethnic or cultural differences of Latin American versus North American and European populations.…”

Section: Discussionmentioning

confidence: 99%

A risk assessment tool (OsteoRisk) for identifying latin American women with osteoporosis

et al. 2005

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OBJECTIVE: To develop a simple and easy-to-use tool for identifying osteoporotic women (femoral neck bone mineral density [BMD] Tscores À 2.5) in Latin America. DESIGN:Retrospective study involving review of medical records.SETTING: Osteoporosis clinics in 6 Latin American countries. PATIENTS:Postmenopausal women ages ! 50 in Latin America who had femoral neck BMD measurements. MEASUREMENTS AND MAIN RESULTS:A risk index was developed from 1,547 patients based on least square regression using age, weight, history of fractures, and other variables as predictors for BMD T-score. The final model was simplified by reducing the number of predictors; sensitivity and specificity were evaluated before and after reducing the number of predictors to assess performance of the index. The final model included age, weight, country, estrogen use, and history of fractures as significant predictors for T-score. The resulting scoring index achieved 91% sensitivity and 47% specificity. Simplifying the index by using only age and weight yielded similar performance (sensitivity, 92%; specificity, 45%). Three risk categories were identified based on OsteoRisk, the index using only age and body weight: high-risk patients (index o =À 2; 65.6% were osteoporotic), moderate-risk patients ( À 2o index o =1; 26.7% were osteoporotic), and low-risk patients (index41; 8% were osteoporotic). Similar results were seen in a validation sample of 279 women in Brazil.CONCLUSION: Age and weight alone performed well for predicting the risk of osteoporosis among postmenopausal women. The OsteoRisk is an easy-to-use tool that effectively targets the vast majority of osteoporotic patients in Latin America for evaluation with BMD. Although patients with fracture should automatically be considered for treatment for osteoporosis, and assessment of bone mineral density (BMD) using dual energy x-ray absorptiometry (DXA) is the standard for diagnosing osteoporosis prior to fracture, facilities for DXA measurements remain limited in Latin America and certain other parts of the world, and this poses a serious challenge for diagnosing osteoporosis in patients without prior fracture.Some researchers have examined the relationship between clinical variables and bone mass in the hope of targeting BMD measurements to patients who are more likely to have osteoporosis.14-20 Lydick et al. 17 developed a model that accurately identifies 90% of subjects with low bone mass and 40% of subjects with normal bone mass. Recently, Koh et al. 18 developed an index, the Osteoporosis Self-assessment Tool for Asians (OSTA), for identifying women at increased risk of osteoporosis in a population of Asian patients other than Japanese. The OSTA is based only on age and weight and achieved a sensitivity of 91% for identifying women with osteoporosis; it was further validated in a cohort of Japanese women, with a sensitivity of 98%. 19 The Osteoporosis Self-assessment Tool (OST) was derived from the OSTA by altering the risk category ranges, and performed well in identifying women at...

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Section: Discussionmentioning

confidence: 99%

A risk assessment tool (OsteoRisk) for identifying latin American women with osteoporosis

et al. 2005

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“…Decision aids based on regression models 18 or involving detailed questionnaires 19 were excluded from this analysis. Our search identified 4 decision rules for BMD testing.…”

Section: Inclusion Of Decision Rules For Referring Women For Bone Denmentioning

confidence: 99%

Evaluation of Decision Rules for Referring Women for Bone Densitometry by Dual-Energy X-ray Absorptiometry

Cadarette

Jaglal²,

Murray³

et al. 2001

JAMA

171

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“…prolonged corticosteroid therapy), an underlying medical condition such as rheumatoid arthritis, and other factors such as low-trauma fracture. As osteoporotic fracture risk is also related to components of bone that are not captured by measuring BMD, as well as to non-skeletal risk factors over and above BMD, 9,33 on an individual basis these risk factors might still be relevant and appropriate selection criteria for the identification of at-risk patients. Therefore, to best guide pharmacists with counselling and in directing appropriate pharmacological treatment, factors such as medication use, medical conditions and history of low-trauma fracture should be incorporated into the risk assessment.…”

Section: Probability and Risk Indexmentioning

confidence: 99%

Refinement of an osteoporosis risk-assessment questionnaire for use in community pharmacy

Poh

Taylor

McAteer

2008

International Journal of Pharmacy Practice

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Objective To explore the influence of bone mineral density (BMD) tests in osteoporosis risk categorisation in community pharmacies, and to develop a simple tool for pharmacists to use as a pre‐BMD test screen. Method A secondary data analysis was conducted on the responses of 193 participants to a risk‐assessment questionnaire, used in previous osteoporosis research that included a BMD test. To explore the impact of the BMD test on pharmacists' categorisation of risk, the researchers made an independent assessment based on responses of the questionnaire. The influence of risk factors on BMD scores/bone status was explored using multiple and logistic regression respectively. Key findings A total of responses of 193 participants were available for study, with 113 in the BMD group and 80 from the non‐BMD group. In the BMD group, both researchers and pharmacists identified a similar proportion of patients in the moderate/high‐risk category when BMD results were incorporated in the risk assessments (X2 = 0.78, degrees of freedom (df) = 1, 0.3 < P < 0.5). A statistically significant difference in risk categorisation was found between the pharmacists and researchers in the non‐BMD group (X2 = 23.9, df = 1, P < 0.001). Risk factors identified to be significantly affecting BMD and of use for identifying patients at high risk for osteopenia/osteoporosis were age, weight, postmenopause and absence of hormone replacement therapy (HRT). These four factors were used to construct a simple risk index to guide pharmacists' initial risk categorisation. Conclusion The findings of this study suggested that BMD testing may increase the effectiveness of risk assessments and enhance the screening procedures in the community pharmacy. The simple risk index could serve as a pre‐BMD test screen, with a BMD test recommended when necessary. A refined risk‐assessment questionnaire could serve to guide pharmacists in directing individualised counselling and advice for at‐risk patients, through identification of modifiable risk factors and conditions.

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Limited Clinical Utility of a Self-Evaluating Risk Assessment Scale for Postmenopausal Osteoporosis: Lack of Predictive Value of Lifestyle-Related Factors

Cited by 14 publications

References 20 publications

A risk assessment tool (OsteoRisk) for identifying latin American women with osteoporosis

A risk assessment tool (OsteoRisk) for identifying latin American women with osteoporosis

Evaluation of Decision Rules for Referring Women for Bone Densitometry by Dual-Energy X-ray Absorptiometry

Refinement of an osteoporosis risk-assessment questionnaire for use in community pharmacy

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