Department of Geriatrics and Gerontology, National Taiwan University Hospital, Taipei, Taiwan; Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
J Formos Med Assoc. 2017 Nov;116(11):888-896. doi: 10.1016/j.jfma.2017.01.003. Epub 2017 Feb 16.
BACKGROUND/PURPOSE: Osteoporosis has been linked to an increased fracture risk and subsequent mortality in the later life. Previous prediction models have focused on osteoporosis in postmenopausal women; however, a prediction tool for osteopenia is needed. Our objective was to establish a prediction model for osteopenia risk in women aged 40-55 years.
This was a cross-sectional study. A total of 1350 Taiwanese women aged 40-55 years were recruited from a health checkup center from 2009 to 2010. The main outcome measure was osteopenia (-1≥bone mineral density T-score > -2.5).
The Osteoporosis Preclinical Assessment Tool (OPAT) developed in this study was based on variables with biological importance to osteopenia and variables that remained significant (p<0.05) in the multivariable analysis, which include age, menopausal status, weight, and alkaline phosphatase level. The OPAT has a total score that ranges from 0 to 7, and categorizes women into high-, moderate-, and low-risk groups. The predictive ability of the OPAT (area under the receiver operating characteristic curve=0.77) was significantly better than that of the Osteoporosis Self-assessment Tool for Asians (area under the receiver operating characteristic curve=0.69). The inclusion of serum total alkaline phosphatase level in the model, which is easy to obtain from routine health checkups, significantly enhanced the sensitivity (McNemar test, p=0.004) for detecting osteopenia in women aged 40-55 years.
Our findings provide an important tool for identifying women at risk of osteoporosis at the preclinical phase.
背景/目的：骨质疏松症与老年人骨折风险增加和随后的死亡率增加有关。以前的预测模型主要集中在绝经后妇女的骨质疏松症上；然而，需要一种骨质疏松症前期的预测工具。我们的目的是建立一个 40-55 岁女性骨质疏松前期风险的预测模型。
这是一项横断面研究。2009 年至 2010 年，我们从一家健康检查中心招募了 1350 名年龄在 40-55 岁的台湾女性。主要结局指标是骨质疏松前期（-1≥骨密度 T 评分>-2.5）。
本研究中开发的骨质疏松前期评估工具（OPAT）基于对骨质疏松前期具有生物学重要性的变量和多变量分析中仍具有统计学意义的变量（p<0.05），这些变量包括年龄、绝经状态、体重和碱性磷酸酶水平。OPAT 的总分为 0 至 7 分，将女性分为高风险、中风险和低风险组。OPAT 的预测能力（受试者工作特征曲线下面积=0.77）明显优于亚洲人骨质疏松症自我评估工具（受试者工作特征曲线下面积=0.69）。模型中纳入了血清总碱性磷酸酶水平，这是从常规健康检查中很容易获得的，这显著提高了检测 40-55 岁女性骨质疏松前期的敏感性（McNemar 检验，p=0.004）。
我们的发现为识别处于骨质疏松前期的女性提供了一个重要的工具。
