Evaluation of decision rules for identifying low bone density in postmenopausal African-American women.

OBJECTIVE: While African-American women tend to have greater bone mineral density (BMD) than caucasian women, they are still at risk of developing osteoporosis later in life. Clinical decision rules (i.e., algorithms) have been developed to assist clinicians identify women at greatest risk of low BMD. However, such tools have only been validated in caucasian and Asian populations. Accordingly, the objective of this study was to compare the performance of five clinical decision rules in identifying postmenopausal African-American women at greatest risk for low femoral BMD. METHODOLOGY: One hundred-seventy-four (n=174) postmenopausal African-American women completed a valid and reliable oral questionnaire to assess lifestyle characteristics, and completed height and weight measures. BMD at the femoral neck was measured via dual energy x-ray absorptiometry (DXA). We calculated sensitivity, specificity, positive predictive value, and negative predictive value for identifying African-American women with low BMD (T-Score < or = -2.0 SD) using five clinical decision rules: Age, Body Size, No Estrogen (ABONE), Osteoporosis Risk Assessment Instrument (ORAI), Osteoporosis Self-Assessment Tool (OST), Simple Calculated Osteoporosis Risk Estimation (SCORE), and body weight less than 70 kg. RESULTS: Approximately 30% of African-American women had low BMD, half of whom had osteoporosis (BMD T-Score < or = -2.5 SD). Sensitivity for identifying women with a low BMD (T-Score < or = -2.0 SD) ranged from 65.57-83.61%, while specificity ranged from 53.85-78.85%. Positive predictive values ranged from 80.95-87.91%, while negative predictive values ranged from 48.44-58.33%. CONCLUSION: Our data suggest that the clinical decision rules analyzed in this study have some usefulness for identifying postmenopausal African-American women with low BMD. However, there is a need to establish cut-points for these clinical decision rules in a larger, more diverse sample of African-American women.