Group of Investigation on Education and Promotion of Health, University of Las Palmas de Gran Canaria, Las Palmas, Canary Islands, Spain.
Calcif Tissue Int. 2012 Aug;91(2):114-20. doi: 10.1007/s00223-012-9616-3. Epub 2012 Jul 1.
Quantitative ultrasound (QUS) of the heel has been proposed as a screening tool to evaluate the bone status and risk of osteoporotic fragility fractures. The aim of this study was to define threshold values that would maximize the predictive ability of QUS to discriminate subjects with vertebral fractures using the classification and regression trees (CART) models. A cross-sectional analysis was made of a cohort of 1,132 postmenopausal women with a mean age of 58 years. A total of 205 women (18.1 %) presented with a history of vertebral fracture. For all patients, a questionnaire of osteoporosis risk factors was given and measurements of the heel QUS and bone mineral density at the lumbar spine and the proximal femur, obtained by dual-energy X-ray absorptiometry (DXA), were made. Spinal radiographs were assessed for vertebral fractures. Sensitivity, specificity, predictive values, likelihood ratios, and receiver operator characteristics (ROC) curve QUS values were calculated using the optimal threshold identified in the CART models. Cutoff values calculated from best CART model (i.e., a QUS index >90.5 %) yielded a sensitivity of 80.3 % (95 % CI 69.2-88.1), a negative predictive value of 94 % (95 % CI 90.1-96.5), and a specificity of 68.8 % (95 % CI 63.3-73.8). This cutoff value would obviate the need to perform DXA in 32.8 % of the women of our population at risk for vertebral fractures. The area under the ROC curve of the best model was 0.8071. QUS was shown to discriminate between women with and without a history of vertebral fracture and constitutes a useful tool for assessing vertebral fracture risk. The application of decision trees (CART analyses) was helpful to define the optimal threshold QUS values.
定量超声（QUS）检测足跟已被提议作为一种筛查工具，用于评估骨状态和骨质疏松性脆性骨折的风险。本研究的目的是确定 QUS 区分有椎体骨折病史的受试者的最佳预测能力的阈值，采用分类回归树（CART）模型。对一个平均年龄为 58 岁的 1132 例绝经后妇女的队列进行了横断面分析。共有 205 名女性（18.1%）有椎体骨折病史。对所有患者进行了骨质疏松症危险因素问卷，并进行了足跟 QUS 测量以及腰椎和股骨近端的骨矿物质密度测量，均采用双能 X 线吸收法（DXA）测量。对脊柱 X 线片进行了椎体骨折评估。使用 CART 模型中确定的最佳阈值计算 QUS 值的灵敏度、特异性、预测值、似然比和受试者工作特征（ROC）曲线。最佳 CART 模型计算的截断值（即 QUS 指数>90.5%）的灵敏度为 80.3%（95%CI 69.2-88.1），阴性预测值为 94%（95%CI 90.1-96.5），特异性为 68.8%（95%CI 63.3-73.8）。该截断值可避免对我们人群中 32.8%有椎体骨折风险的妇女进行 DXA 检查。最佳模型的 ROC 曲线下面积为 0.8071。QUS 能够区分有和无椎体骨折病史的妇女，是评估椎体骨折风险的有用工具。决策树（CART 分析）的应用有助于确定最佳的 QUS 阈值值。
