目的 利用基本公共卫生服务体检数据,通过Meta分析构建普适于中老年人群的2型糖尿病(diabetes mellitus type 2,T2DM)logistic函数风险预测模型.方法 模型构建:计算机检索中英文数据库关于T2DM危险因素的队列研究,Meta合并危险因素效应值(odds ratio,OR),转换为logistic函数的偏回归系数β;常数项α通过合并各队列研究的发病率进行估计.模型验证:使用受试者操作特征(receiver operator characteristic,ROC)曲线,以成都市某社区卫生服务中心2017年-2022年7 602名初次体检未患T2DM者的基公卫体检随访数据验证模型预测效果.结果 危险因素Meta分析具有统计学意义的基公卫体检条目有10个,来自40项队列研究,分别为年龄、中心性肥胖、吸烟、缺乏运动、空腹血糖受损、低高密度脂蛋白胆固醇(high-density lipoprotein cholesterol,HDL-C)、高血压、体质量指数(body mass index,BMI)、甘油三酯-葡萄糖(triglyceride glucose,TYG)指数和糖尿病家族史,OR(95%置信区间)为1.04(1.03,1.05)、1.55(1.29,1.88)、1.36(1.11,1.66)、1.26(1.07,1.49)、3.93(2.94,5.24)、1.14(1.06,1.23)、1.47(1.34,1.61)、1.11(1.05,1.18)、2.15(1.75,2.62)、1.66(1.55,1.78);37项研究报告了发病率,合并发病率(95%置信区间)为0.08(0.07,0.09),常数α为-2.442.将构建的T2DM风险预测模型在7 602例基公卫体检数据中进行外部验证,曲线下面积(95%置信区间)为0.794(0.771,0.816).结论 利用基公卫健康体检数据构建的T2DM风险预测模型具有较好的预测性能,可作为中老年人群T2DM风险预测的实用工具.
Construction of a Predictive Model for Diabetes Mellitus Type 2 in Middle-Aged and Elderly Populations Based on the Medical Checkup Data of National Basic Public Health Service
Objective To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2(T2DM)in the middle-aged and elderly populations based on the results of a Meta-analysis,and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service.Methods Cohort studies evaluating T2DM risks were identified in Chinese and English databases.The logistic model utilized Meta-combined effect values such as the odds ratio(OR)to derive β,the partial regression coefficient,of the logistic model.The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model.Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service.The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7 602 individuals who did not have T2DM at their baseline medical checkups done at the community health center.This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people.Results A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM,including age,central obesity,smoking,physical inactivity,impaired fasting glucose,a reduced level of high-density lipoprotein cholesterol(HDL-C),hypertension,body mass index(BMI),triglyceride glucose(TYG)index,and a family history of diabetes,with the OR values and 95% confidence interval(CI)being 1.04(1.03,1.05),1.55(1.29,1.88),1.36(1.11,1.66),1.26(1.07,1.49),3.93(2.94,5.24),1.14(1.06,1.23),1.47(1.34,1.61),1.11(1.05,1.18),2.15(1.75,2.62),and 1.66(1.55,1.78),respectively,and the combined β values being 0.039,0.438,0.307,0.231,1.369,0.131,0.385,0.104,0.765,and 0.507,respectively.A total of 37 studies reported the incidence rate,with the combined incidence being 0.08(0.07,0.09)and the parameter α being-2.442 for the logistic model.The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7 602 individuals who had medical checkups and were followed up for at least once.External validation results showed that the predictive model had an area under curve(AUC)of 0.794(0.771,0.816),accuracy of 74.5%,sensitivity of 71.0%,and specificity of 74.7% in the 7 602 individuals.Conclusion The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.
Diabetes mellitus,Type 2Risk predictionBasic public health serviceMiddle-aged and elderly populations
国家科技期刊平台
NSTL
万方数据
