Development and validation of osteoporosis risk-assessment model for Korean postmenopausal women
Development and validation of osteoporosis risk-assessment model for Korean postmenopausal women
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DOI：
10.1007/s00774-013-0426-0
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发表时间：
2013-07-01
影响因子：
3.3
通讯作者：
Kim, Hyeon Chang
中科院分区：
文献类型：
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作者：
Oh, Sun Min;Nam, Byung-Ho;Kim, Hyeon Chang
目前，双能X线骨密度仪(DXA)是检测骨质疏松症的金标准，但不推荐用于普通人群筛查。因此，本研究旨在开发一种骨质疏松症风险评估模型，以识别韩国绝经后妇女中的高危个体。分别有1,209名和1,046名绝经后妇女分别参加了2009年和2010年的韩国国民健康和营养检查调查，数据被用于开发和验证骨质疏松症风险评估模型。骨质疏松症的定义是股骨颈或腰椎的T评分小于或等于-2.5。比较候选模型和亚洲人骨质疏松症自我评估工具(OSTA)在敏感性、特异性和受试者工作特征曲线下面积(AUC)方面的表现。为了比较韩国骨质疏松症风险评估模型(KORAM)和OSTA，进一步计算了净重分类改进。在发展数据集中，骨质疏松症的患病率为33.9%。由年龄、体重和激素治疗组成的Koram的敏感度为91.2%，特异度为50.6%，AUC值为0.709，特异度为-9。在验证数据集中显示了可比较的结果：敏感度84.8%，特异度51.6%，AUC 0.682。此外，Koram的风险分类显示，与OSTA的风险分类相比，重新分类的比例从7.4%提高到41.7%。可兰姆可以很容易地用作预先筛选工具，以确定DXA测试的候选人。需要对其他数据集的成本效益和可复制性进行进一步研究，以确定Koram的临床实用价值。
Currently, dual-energy X-ray absorptiometry (DXA) is the gold standard for detecting osteoporosis, but is not recommended for general population screening. Therefore, this study aims to develop an osteoporosis risk-assessment model to identify high-risk individuals among Korean postmenopausal women. Data from 1,209 and 1,046 postmenopausal women who participated in the 2009 and 2010 Korean National Health and Nutrition Examination Survey, respectively, were used for development and validation of an osteoporosis risk-assessment model. Osteoporosis was defined as T score less than or equal to -2.5 at either the femoral neck or lumbar spine. Performance of the candidate models and the Osteoporosis Self assessment Tool for Asians (OSTA) were compared with respect to sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). To compare the developed Korean Osteoporosis Risk-Assessment Model (KORAM) with OSTA, a net reclassification improvement was further calculated. In the development dataset, the prevalence of osteoporosis was 33.9 %. KORAM, consisting of age, weight, and hormone therapy, had a sensitivity of 91.2 %, a specificity of 50.6 %, and an AUC of 0.709 with a specific cut-off score of -9. Comparable results were shown in the validation dataset: sensitivity 84.8 %, specificity 51.6 %, and AUC 0.682. Additionally, risk categorization with KORAM showed improved reclassification over that of OSTA from 7.4 to 41.7 %. KORAM can be easily used as a pre-screening tool to identify candidates for DXA tests. Further studies investigating cost-effectiveness and replicability in other datasets are required to establish the clinical utility of KORAM.