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Karen F. Mauck, MD, MSc; Maria-Teresa Cuddihy, MD, MPH; Elizabeth J. Atkinson, MSc; L. Joseph Melton III, MD, MPH

Arch Intern Med. 2005;165:530-536.

Background  Osteoporosis clinical prediction rules attempt to identify the postmenopausal women in whom, on the basis of individual risk factors, bone densitometry will detect low bone mass. We assessed and compared the diagnostic properties of the following 3 osteoporosis clinical prediction rules: the Simple Calculated Osteoporosis Risk Estimation, Osteoporosis Risk Assessment Instrument, and National Osteoporosis Foundation practice guidelines.

Methods  Secondary data analysis of an existing population-based sample of postmenopausal women 45 years or older (N = 202) in Rochester, Minn.

Results  Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values, and positive (LR+) and negative (LR–) likelihood ratios were calculated using the World Health Organization diagnosis of osteoporosis as the reference standard. The Simple Calculated Osteoporosis Risk Estimation had a sensitivity of 100%, specificity of 29%, PPV of 27%, NPV of 100%, LR+ of 1.4, and LR– of 0. The Osteoporosis Risk Assessment Instrument had a sensitivity of 98%, specificity of 40%, PPV of 29%, NPV of 77%, LR+ of 1.4, and LR– of 0.4. The National Osteoporosis Foundation practice guidelines had a sensitivity of 100%, specificity of 10%, PPV of 27%, NPV of 100%, LR+ of 1.1, and LR– of 0. The Simple Calculated Osteoporosis Risk Estimation and Osteoporosis Risk Assessment Instrument were much more specific in postmenopausal women younger than 65 years compared with those 65 years or older.

Conclusions  Our results suggest that these clinical prediction rules do not perform well as a general screening method to identify postmenopausal women who are more likely to have osteoporosis; however, the Osteoporosis Risk Assessment Instrument and Simple Calculated Osteoporosis Risk Estimation may be useful in identifying some women who need not undergo testing, especially younger postmenopausal women.

Author Affiliations: Division of General Internal Medicine, Department of Internal Medicine (Dr Mauck), and Divisions of Biostatistics (Ms Atkinson) and Epidemiology (Dr Melton), Department of Health Sciences Research, Mayo Clinic and Mayo Foundation, Rochester, Minn; and Division of General Medicine and Primary Care, Department of Internal Medicine, Beth Israel Deaconess Medical Center, Boston, Mass (Dr Cuddihy).

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