Using clinical risk factors and bone mineral density to determine who among patients undergoing bone densitometry should have vertebral fracture assessment
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Using clinical risk factors and bone mineral density to determine who among patients undergoing bone densitometry should have vertebral fracture assessment

Abstract

Vertebral fracture assessment (VFA) is a new method for imaging thoracolumbar spine on bone densitometer. Among patients referred for bone densitometry, the selection of patients for VFA testing can be optimized using an index derived from clinical risk factors and bone density measurement. VFA, a method for imaging thoracolumbar spine on bone densitometer, was developed because vertebral fractures, although common and predictive of future fractures, are often not clinically diagnosed. The study objective was to develop a strategy for selecting patients for VFA. A convenience sample from a university hospital bone densitometry center included 892 subjects (795 women) referred for bone mineral density (BMD) testing. We used questionnaires to capture clinical risk factors and dual-energy X-ray absorptiometry to obtain BMD and VFA. Prevalence of vertebral fractures was 18% in women and 31% in men (p = 0.003 for gender difference). In women, age, height loss, glucocorticoid use, history of vertebral and other fractures, and BMD T-score were significantly and independently associated with vertebral fractures. A multivariate model which included above predictors had an area under the receiver operating curve of 0.85 with 95% confidence interval (CI) of 0.81 to 0.89. A risk factor index was derived from the above multivariate model. Using a level of 2 as a cut-off yielded 93% sensitivity (95% CI 87, 96) and 48% specificity (95% CI 69, 83). Assuming a 15% prevalence of vertebral fractures, this cut-off value had a 24% positive and 97% negative predictive value and required VFA scanning of three women at a cost of $60 (assuming a $20 cost/VFA scan) to detect one with vertebral fracture(s). Selecting patients for VFA can be optimized using an index derived from BMD measurement and easily obtained clinical risk factors.

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