北京老年男性糖尿病风险积分的探讨和应用

Investigation and application of a diabetes risk score in predicting incident diabetes in male senile people in Beijing

目的 尝试建立北京老年男性的糖尿病风险积分（DRS）以预测个体未来糖尿病发生的风险.方法 依据试验组1 370例（年龄为48～87岁）非糖尿病男性患者随访10年的队列资料,运用多元logistic逐步回归建立DRS,同时在检验组340例（年龄为43～88岁）非糖尿病男性患者随访10年的队列资料中进行检验.结果 受试者工作特征（ROC）曲线分析显示曲线下面积（AUC）最大的DRS模型包括年龄、高血压史、既往高血糖史、体重指数、空腹血糖、甘油三酯和高密度脂蛋白胆固醇（HDL-C）,以此模型建立DRS积分系统,累积分值范围为0～12,4为最佳切点,此积分在试验组和检验组中的AUC分别0.726（95%CI0.692～0.759）和0.765（95%CI 0.691～0.839）,敏感性分别为65.3%和68.1%,特异性分别为70.0%和64.8%,阳性预测值分别为37.0%和23.2%,阴性预测值分别为88.2%和94.1%.结论 此DRS结合了一般临床信息、血糖和血脂,对未来糖尿病具有较好的预测效能.

Objective To develop a diabetes risk score （DRS）to predict the risk of development of incident diabetes in male senile people in Beijing. Methods DRS was developed basing on a test group including a cohort of 1 370 individuals aged 48-87 years without diabetes at baseline, followed for 10 years by Logistic regression and validated on a value group including a cohort of 340 individuals aged 43-88 years without diabetes at baseline. Results The model with the highest area under the ROC curve （ AUC ） included age, hypertension,history of hyperglycemia, body mass index, fasting plasma glucose, triglycerides, and high-density lipoproteincholesterol （HDL-C）. DRS was developed basing on this model with a range from 0 to 12 and an optimal cut-off of 4. AUC were respectively 0. 726 （ 95% CI0. 692-0. 759 ） and 0. 765 （ 95% CI0. 691-0. 839 ） in test group and validation group. The sum score value ≥4 had sensitivity of 65.3% and 68. 1%, specificity of 70. 0% and 64.8%, positive predictive value of 37.0% and 23.2%, negative predictive value of 88.2% and 94. 1%.Conclusion The DRS, derived from clinical information combined with plasma glucose and lipids, is an effective tool to predict incident diabetes.