Margaret L Gourlay1, Victor S Ritter2, Jason P Fine2, Robert A Overman3, John T Schousboe4,5, Peggy M Cawthon6, Eric S Orwoll7, Tuan V Nguyen8,9, Nancy E Lane10, Steven R Cummings6, Deborah M Kado11,12, Jodi A Lapidus13, Susan J Diem14,15, Kristine E Ensrud14,15,16. 1. Department of Family Medicine, University of North Carolina, Aycock Building, Manning Drive, CB #7595, UNC-Chapel Hill, Chapel Hill, NC, 27599-7595, USA. margaret_gourlay@med.unc.edu. 2. Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA. 3. NoviSci, LLC, Durham, NC, USA. 4. Department of Rheumatology, Park Nicollet Health Services, Minneapolis, MN, USA. 5. Division of Health Policy and Management, University of Minnesota, Minneapolis, MN, USA. 6. Research Institute, California Pacific Medical Center, San Francisco, CA, USA. 7. Bone and Mineral Unit, Oregon Health and Science University, Portland, OR, USA. 8. Garvan Institute of Medical Research, UNSW School of Public Health and Community Medicine, Kensington, NSW, Australia. 9. Centre for Health Technologies, University of Technology, Sydney, Australia. 10. Division of Rheumatology, Department of Medicine, Center for Musculoskeletal Health, UC Davis Health System, Sacramento, CA, USA. 11. Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA. 12. Department of Medicine, University of California, San Diego, La Jolla, CA, USA. 13. School of Public Health, Oregon Health and Science University, Portland, OR, USA. 14. Department of Medicine, University of Minnesota, Minneapolis, MN, USA. 15. Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA. 16. Center for Chronic Disease Outcomes Research, VA Health Care System, Minneapolis, MN, USA.
Abstract
Femoral neck bone mineral density (BMD), age plus femoral neck BMD T score, and three externally generated fracture risk tools had similar accuracy to identify older men who developed osteoporotic fractures. Risk tools with femoral neck BMD performed better than those without BMD. The externally developed risk tools were poorly calibrated. INTRODUCTION: We compared the performance of fracture risk assessment tools in older men, accounting for competing risks including mortality. METHODS: A comparative ROC curve analysis assessed the ability of the QFracture, FRAX® and Garvan fracture risk tools, and femoral neck bone mineral density (BMD) T score with or without age to identify incident fracture in community-dwelling men aged 65 years or older (N = 4994) without hip or clinical vertebral fracture or antifracture treatment at baseline. RESULTS: Among risk tools calculated with BMD, the discriminative ability to identify men with incident hip fracture was similar for FRAX (AUC 0.77, 95% CI 0.73, 0.81), the Garvan tool (AUC 0.78, 95% CI 0.74, 0.82), age plus femoral neck BMD T score (AUC 0.79, 95% CI 0.75, 0.83), and femoral neck BMD T score alone (AUC 0.76, 95% CI 0.72, 0.81). Among risk tools calculated without BMD, the discriminative ability to identify hip fracture was similar for QFracture (AUC 0.69, 95% CI 0.66, 0.73), FRAX (AUC 0.70, 95% CI 0.66, 0.73), and the Garvan tool (AUC 0.71, 95% CI 0.67, 0.74). Correlated ROC curve analyses revealed better diagnostic accuracy for risk scores calculated with BMD compared with QFracture (P < 0.0001). Calibration was good for the internally generated BMD T score predictor with or without age and poor for the externally developed risk tools. CONCLUSION: In untreated older men without fragility fractures at baseline, an age plus femoral neck BMD T score classifier identified men with incident hip fracture as accurately as more complicated fracture risk scores.
Femoral neck bone mineral density (BMD), age plus femoral neck BMD T score, and three externally generated fracture risk tools had similar accuracy to identify older men who developed osteoporotic fractures. Risk tools with femoral neck BMD performed better than those without BMD. The externally developed risk tools were poorly calibrated. INTRODUCTION: We compared the performance of fracture risk assessment tools in older men, accounting for competing risks including mortality. METHODS: A comparative ROC curve analysis assessed the ability of the QFracture, FRAX® and Garvan fracture risk tools, and femoral neck bone mineral density (BMD) T score with or without age to identify incident fracture in community-dwelling men aged 65 years or older (N = 4994) without hip or clinical vertebral fracture or antifracture treatment at baseline. RESULTS: Among risk tools calculated with BMD, the discriminative ability to identify men with incident hip fracture was similar for FRAX (AUC 0.77, 95% CI 0.73, 0.81), the Garvan tool (AUC 0.78, 95% CI 0.74, 0.82), age plus femoral neck BMD T score (AUC 0.79, 95% CI 0.75, 0.83), and femoral neck BMD T score alone (AUC 0.76, 95% CI 0.72, 0.81). Among risk tools calculated without BMD, the discriminative ability to identify hip fracture was similar for QFracture (AUC 0.69, 95% CI 0.66, 0.73), FRAX (AUC 0.70, 95% CI 0.66, 0.73), and the Garvan tool (AUC 0.71, 95% CI 0.67, 0.74). Correlated ROC curve analyses revealed better diagnostic accuracy for risk scores calculated with BMD compared with QFracture (P < 0.0001). Calibration was good for the internally generated BMD T score predictor with or without age and poor for the externally developed risk tools. CONCLUSION: In untreated older men without fragility fractures at baseline, an age plus femoral neck BMD T score classifier identified men with incident hip fracture as accurately as more complicated fracture risk scores.
Entities:
Keywords:
Bone density; Fractures; Male; Osteoporosis; Risk assessment
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