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Osteoporos Int. 1993 May;3(3):120-6.

Predicting vertebral fracture incidence from prevalent fractures and bone density among non-black, osteoporotic women.

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  • 1Hawaii Osteoporosis Center, Honolulu 96814.

Abstract

We evaluated the ability of bone density and vertebral fractures at baseline to predict vertebral fracture incidence in a cohort of postmenopausal women with osteoporosis. The study population was 380 postmenopausal women (mean age 65 years) treated for osteoporosis in a randomized, placebo-controlled, clinical trial of the bisphosphonate etidronate at seven geographic centers in the United States. Baseline measurements of bone mineral density were obtained in 1986 by quantitative computed tomography at the spine and dual-photon absorptiometry at the lumbar spine and hip. Vertebral fractures were documented on serial spine radiographs. Proportional hazards models were used to evaluate the ability to predict the risk of subsequent fractures during an average of 2.9 years of follow-up. Presence of one or two fractures increased the rate of new vertebral fractures 7.4-fold (95% confidence interval = 1.0 to 55.9). Additional fractures at baseline further increased the fracture rate. A decrease of 2 standard deviations in spinal bone density by absorptiometry was associated with a 5.8-fold increase in fracture rate (95% confidence interval = 2.9 to 11.6). The lowest and highest quintiles of bone density had absolute fracture rates of 120 and 6 cases per 1000 patient-years, respectively. In general, the simultaneous use of two predictors (bone density and prevalent fractures or two bone density measurements) improved fracture prediction, compared with the use of a single predictor. We conclude that both bone density and prevalent vertebral fractures are strong, complementary predictors of vertebral fracture risk. The results suggest that physicians can use bone density and prevalent vertebral fractures, individually or in combination, as risk factors to identify patients at greatest risk of new fractures.

PMID:
8481587
[PubMed - indexed for MEDLINE]
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