Classification of Osteoporosis Based on Bone Mineral Densities

Authors

  • Ying Lu,

    1. Osteoporosis and Arthritis Research Group, Department of Radiology, University of California San Francisco, San Francisco, California, USA
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  • Harry K. Genant,

    Corresponding author
    1. Osteoporosis and Arthritis Research Group, Department of Radiology, University of California San Francisco, San Francisco, California, USA
    • Address reprint requests to: Harry K. Genant, M.D., Department of Radiology, University of California, San Francisco, San Francisco, CA 94143-0628, USA
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  • John Shepherd,

    1. Osteoporosis and Arthritis Research Group, Department of Radiology, University of California San Francisco, San Francisco, California, USA
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  • Shoujun Zhao,

    1. Osteoporosis and Arthritis Research Group, Department of Radiology, University of California San Francisco, San Francisco, California, USA
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  • Ashwini Mathur,

    1. Statistical Sciences, SmithKline Beecham Pharmaceuticals, King of Prussia, Pennsylvania, USA
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  • Thomas P. Fuerst,

    1. Osteoporosis and Arthritis Research Group, Department of Radiology, University of California San Francisco, San Francisco, California, USA
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  • Steven R. Cummings

    1. Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
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Abstract

In this article we examine the role of bone mineral density (BMD) in the diagnosis of osteoporosis. Using information from 7671 women in the Study of Osteoporotic Fractures (SOF) with BMD measurements at the proximal femur, lumbar spine, forearm, and calcaneus, we examine three models with differing criteria for the diagnosis of osteoporosis. Model 1 is based on the World Health Organization (WHO) criteria using a T score of −2.5 relative to the manufacturers' young normative data aged 20-29 years, with modifications using information from the Third National Health and Nutrition Examination Survey (NHANES). Model 2 uses a T score of −1 relative to women aged 65 years at the baseline of the SOF population. Model 3 classifies women as osteoporotic if their estimated osteoporotic fracture risk (spine and/or hip) based on age and BMD is above 14.6%. We compare the agreement in osteoporosis classification according to the different BMD measurements for the three models. We also consider whether reporting additional BMD parameters at the femur or forearm improves risk assessment for osteoporotic fractures. We observe that using the WHO criteria with the manufacturers' normative data results in very inconsistent diagnoses. Only 25% of subjects are consistently diagnosed by all of the eight BMD variables. Such inconsistency is reduced by using a common elderly normative population as in model 2, in which case 50% of the subjects are consistently diagnosed as osteoporotic by all of the eight diagnostic methods. Risk-based diagnostic criteria as in model 3 improve consistency substantially to 68%. Combining the results of BMD assessments at more than one region of interest (ROI) from a single scan significantly increases prediction of hip and/or spine fracture risk and elevates the relative risk with increasing number of low BMD subregions. We conclude that standardization of normative data, perhaps referenced to an older population, may be necessary when applying T scores as diagnostic criteria in patient management. A risk-based osteoporosis classification does not depend on the manufacturers' reference data and may be more consistent and efficient for patient diagnosis.

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