Wilson Peter W F, Meigs James B, Sullivan Lisa, Fox Caroline S, Nathan David M, D'Agostino Ralph B
Emory Program in Cardiovascular Outcomes Research and Epidemiology, Emory University School of Medicine, Atlanta, GA 30306, USA.
Arch Intern Med. 2007 May 28;167(10):1068-74. doi: 10.1001/archinte.167.10.1068.
Prediction rules for type 2 diabetes mellitus (T2DM) have been developed, but we lack consensus for the most effective approach.
We estimated the 7-year risk of T2DM in middle-aged participants who had an oral glucose tolerance test at baseline. There were 160 cases of new T2DM, and regression models were used to predict new T2DM, starting with characteristics known to the subject (personal model, ie, age, sex, parental history of diabetes, and body mass index [calculated as the weight in kilograms divided by height in meters squared]), adding simple clinical measurements that included metabolic syndrome traits (simple clinical model), and, finally, assessing complex clinical models that included (1) 2-hour post-oral glucose tolerance test glucose, fasting insulin, and C-reactive protein levels; (2) the Gutt insulin sensitivity index; or (3) the homeostasis model insulin resistance and the homeostasis model insulin resistance beta-cell sensitivity indexes. Discrimination was assessed with area under the receiver operating characteristic curves (AROCs).
The personal model variables, except sex, were statistically significant predictors of T2DM (AROC, 0.72). In the simple clinical model, parental history of diabetes and obesity remained significant predictors, along with hypertension, low levels of high-density lipoprotein cholesterol, elevated triglyceride levels, and impaired fasting glucose findings but not a large waist circumference (AROC, 0.85). Complex clinical models showed no further improvement in model discriminations (AROC, 0.850-0.854) and were not superior to the simple clinical model.
Parental diabetes, obesity, and metabolic syndrome traits effectively predict T2DM risk in a middle-aged white population sample and were used to develop a simple T2DM prediction algorithm to estimate risk of new T2DM during a 7-year follow-up interval.
2型糖尿病（T2DM）的预测规则已经制定出来，但我们对于最有效的方法尚未达成共识。
我们对在基线时进行口服葡萄糖耐量试验的中年参与者的T2DM 7年风险进行了评估。共有160例新诊断的T2DM病例，采用回归模型预测新的T2DM，首先使用受试者已知的特征（个人模型，即年龄、性别、糖尿病家族史和体重指数[计算方法为体重（千克）除以身高（米）的平方]），然后加入包括代谢综合征特征的简单临床测量指标（简单临床模型），最后评估包括以下内容的复杂临床模型：（1）口服葡萄糖耐量试验后2小时血糖、空腹胰岛素和C反应蛋白水平；（2）古特胰岛素敏感性指数；或（3）稳态模型胰岛素抵抗和稳态模型胰岛素抵抗β细胞敏感性指数。通过受试者操作特征曲线下面积（AROC）评估辨别能力。
除性别外，个人模型变量是T2DM的统计学显著预测因素（AROC，0.72）。在简单临床模型中，糖尿病家族史和肥胖仍然是显著的预测因素，同时还有高血压、高密度脂蛋白胆固醇水平低、甘油三酯水平升高和空腹血糖受损，但腰围增大不是（AROC，0.85）。复杂临床模型在模型辨别能力方面没有进一步改善（AROC，0.850 - 0.854），且不优于简单临床模型。
糖尿病家族史、肥胖和代谢综合征特征可有效预测中年白人人群样本中的T2DM风险，并用于开发一种简单的T2DM预测算法，以估计7年随访期间新T2DM的风险。
