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中国台湾省35~74岁健检人群慢性肾病5年发病风险预测模型
引用本文:孙凤,郁凯,陶庆梅,陶秋山,杨兴华,曹纯铿,詹思延. 中国台湾省35~74岁健检人群慢性肾病5年发病风险预测模型[J]. 中国预防医学杂志, 2013, 0(1): 47-52
作者姓名:孙凤  郁凯  陶庆梅  陶秋山  杨兴华  曹纯铿  詹思延
作者单位:北京大学公卫学院流行病与卫生统计学系;北京大学药学院药事管理与临床药学系;新疆石河子大学医学院预防医学系;天津市第五中心医院骨科;首都医科大学公共卫生与家庭医学学院;美兆健康管理机构
摘    要:目的构建中国台湾省35~74岁健检人群慢性肾病(CKD)5年发病风险(个体化)预测模型。方法选择1996~2006年初次参加台湾省美兆健检的35~74岁人群19 987人,将其中基线未患CKD者18 275人分为建模队列(用于建立5年发病预测模型)和验证队列(用于评估模型外部效度)。采用logistic回归构建预测模型,以ROC曲线下面积(AUC)评价拟合优度,并将人群的预测风险概率进行风险等级划分。结果去除基线患者后CKD5年发病率为5.24%(958/18275)。纳入5年发病风险预测模型的变量包括年龄、教育程度、糖尿病、高血压、低密度脂蛋白胆固醇、甘油三酯和血肌酐水平7个指标。建模队列建立的预测模型的ROC曲线下面积(AUC)约为0.734(95%CI:0.714~0.754),验证队列外部效度验证结果AUC=0.768(95%CI:0.734~0.801)。将建模队列划分为4个风险等级后,显示中危(占14.1%)和高危(占5.4%)的个体5年内发生CKD的危险分别比一般人群高2.0倍和4.8倍。结论利用中国台湾省美兆健检纵向数据建立的CKD 5年个体风险预测模型效应与信度均较高,且简单实用,对于今后CKD风险个体评价及群体监测均有较大的应用价值。

关 键 词:慢性肾病  风险预测模型  纵向数据  健检

Estimated risks on developing chronic kidney disease within 5 years for adults aged 35-74 based on Taiwan MJ health-checkup Database
SUN Feng,YU Kai,TAO Qing-mei,TAO Qiu-shan,YANG Xing-hua,CAO Chun-keng,ZHAN Si-yan. Estimated risks on developing chronic kidney disease within 5 years for adults aged 35-74 based on Taiwan MJ health-checkup Database[J]. China Preventive Medicine, 2013, 0(1): 47-52
Authors:SUN Feng  YU Kai  TAO Qing-mei  TAO Qiu-shan  YANG Xing-hua  CAO Chun-keng  ZHAN Si-yan
Affiliation:Department of Epidemiology and Biostatistics,School of Public Health, Peking University,Beijing 100191,China
Abstract:Objective The purpose of this study was to provide the epidemiological model evaluating the risks of developing chronic kidney disease(CKD)within 5 years among adults in Taiwan.Methods After excluding 1 712 individuals with CKD at baseline,a cohort of 18 275 subjects aged 35-74 years without CKD in the checkup point were enrolled during the year of 1996 to 2006.They were divided into a modeling cohort(for risk factors)and a verifying cohort(for evaluation).Logistic regression models was used for the estimation of risk factors,and the area under the receiver-operating characteristic(ROC)curve(AUC)was applied for the evaluation of model predictability as well as the verification of its diagnostic property for the verifying cohort.A total of 4 different risk levels were classified based on cut points of these probabilities after transforming into normal distribution by log-transformation.Results After excluding 1 712 CKD individuals at baseline,the incidence of CKD was found to be 5.24%(958/18 275)in 5 years.Age,education,diabetes,hypertension,triglyceride,low density lipoprotein cholesterol and serum creatinine were 7 variables included in Logistic regression model for the estimation of risk factors.The results showed that the AUC was 0.734(95%CI: 0.714-0.754)for modeling cohort and 0.768(95%CI:0.734-0.801)for verifying cohort.Also individuals who were in the intermediate(14.1%)and high(5.4)risk levels were 2 times and 4.8 times more likely to develop CKD in 5 years.Conclusions The CKD Risk Score model has higher predictability and reliability and is practicable,which can be used for CKD risk evaluation for both individual and community.
Keywords:Chronic kidney disease  Risk predictive model  Longitudinal data  Health-checkup
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