Clinical performance of osteoporosis risk assessment tools in women aged 67 years and older
- M. L. Gourlay,
- J. M. Powers,
- L.-Y. Lui,
- K. E. Ensrud,
- for the Study of Osteoporotic Fractures Research Group
- … show all 5 hide
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Clinical performance of osteoporosis risk assessment tools was studied in women aged 67 years and older. Weight was as accurate as two of the tools to detect low bone density. Discriminatory ability was slightly better for the OST risk tool, which is based only on age and weight.
Screening performance of osteoporosis risk assessment tools has not been tested in a large, population-based US cohort.
We conducted a diagnostic accuracy analysis of the Osteoporosis Self-assessment Tool (OST), Osteoporosis Risk Assessment Instrument (ORAI), Simple Calculated Osteoporosis Risk Estimation (SCORE), and individual risk factors (age, weight or prior fracture) to identify low central (hip and lumbar spine) bone mineral density (BMD) in 7779 US women aged 67 years and older participating in the Study of Osteoporotic Fractures.
The OST had the greatest area under the receiver operating characteristic curve (AUC 0.76, 95% CI 0.74, 0.77). Weight had an AUC of 0.73 (95% CI 0.72, 0.75), which was ≥AUC values for the ORAI, SCORE, age or prior fracture. Using cut points from the development papers, the risk tools had sensitivities ≥85% and specificities ≤48%. When new cut points were set to achieve a likelihood ratio of negative 0.1–0.2, the tools ruled out fewer than 1/4 of women without low central BMD.
Weight identified low central BMD as accurately as the ORAI and SCORE. The risk tools would be unlikely to show an advantage over simple weight cut points in an osteoporosis screening protocol for elderly women.
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- Clinical performance of osteoporosis risk assessment tools in women aged 67 years and older
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- Author Affiliations
- 1. Department of Family Medicine, University of North Carolina, Chapel Hill, NC, USA
- 5. Aycock Building, Manning Drive, CB #7595, UNC-Chapel Hill, Chapel Hill, NC, 27599-7595, USA
- 2. Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
- 3. Research Institute, California Pacific Medical Center, San Francisco, CA, USA
- 4. Department of Medicine and Division of Epidemiology, University of Minnesota, VA Medical Center, Minneapolis, MN, USA