Wang Kun, Yang Qun-Fang, Chen Xing-Lin, Liu Yu-Wei, Shan Sheng-Shuai, Zheng Hua-Bo, Zhao Xiao-Fang, Chen Chang-Zhong, Liu Cheng-Yun
Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Hyperbaric Oxygen Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Int J Endocrinol. 2018 Dec 13;2018:9376179. doi: 10.1155/2018/9376179. eCollection 2018.
It has well established that metabolic syndrome (MetS) can predict the risk of type 2 diabetes mellitus (T2DM) in some population groups. However, limited evidence is available regarding the predictive effect of MetS for incident T2DM in mainland Chinese population.
A 3-year cohort study was performed for 9735 Chinese without diabetes at baseline. MetS and its components were assessed by multivariable analysis using Cox regression. Prediction models were developed. Discrimination was assessed with area under the receiver operating characteristic curves (AUCs), and performance was assessed by a calibration curve.
The 3-year cumulative incidence of T2DM was 11.29%. Baseline MetS was associated with an increased risk of T2DM after adjusting for age (HR = 2.68, 95% CI, 2.27-3.17 in males; HR = 2.59, 95% CI, 1.83-3.65 in females). Baseline MetS exhibited relatively high specificity (88% in males, 94% in females) and high negative predictive value (90% in males, 94% in females) but low sensitivity (36% in males, 23% in females) and low positive predictive value (31% in males and females) for predicting the 3-year risk of T2DM. AUCs, including age and components of MetS, for the prediction model were 0.779 (95% CI: 0.759-0.799) in males and 0.860 (95% CI: 0.836-0.883) in females. Calibration curves revealed good agreement between prediction and observation results in males; however, the model could overestimate the risk when the predicted probability is >40% in females.
MetS predicts the risk of T2DM. The quantitative MetS-based prediction model for T2DM risk may improve preventive strategies for T2DM and present considerable public health benefits for the people in mainland China.
代谢综合征（MetS）能够预测某些人群患2型糖尿病（T2DM）的风险，这一点已得到充分证实。然而，关于MetS对中国大陆人群新发T2DM的预测作用，相关证据有限。
对9735名基线时无糖尿病的中国人进行了一项为期3年的队列研究。使用Cox回归通过多变量分析评估MetS及其组分。构建了预测模型。通过受试者工作特征曲线下面积（AUC）评估辨别力，并通过校准曲线评估性能。
T2DM的3年累积发病率为11.29%。在校正年龄后，基线MetS与T2DM风险增加相关（男性HR = 2.68，95%CI为2.27 - 3.17；女性HR = 2.59，95%CI为1.83 - 3.65）。基线MetS在预测T2DM的3年风险时表现出相对较高的特异性（男性为88%，女性为94%）和较高的阴性预测值（男性为90%，女性为94%），但敏感性较低（男性为36%，女性为23%）和阳性预测值较低（男性和女性均为31%）。包括年龄和MetS组分的预测模型的AUC在男性中为0.779（95%CI：0.759 - 0.799），在女性中为0.860（95%CI：0.836 - 0.883）。校准曲线显示男性的预测结果与观察结果之间具有良好的一致性；然而，当预测概率>40%时，该模型可能高估女性的风险。
MetS可预测T2DM风险。基于MetS的T2DM风险定量预测模型可能会改善T2DM的预防策略，并为中国大陆人群带来可观的公共卫生效益。
