Abstract
陈金宏,吴海云,何昆仑,何耀,秦银河.老年男性人群缺血性心脑血管病预测模型的建立[J].Chinese journal of Epidemiology,2010,31(10):1166-1169
老年男性人群缺血性心脑血管病预测模型的建立
Establishment of the prediction modeI for ischemic cardiovascular disease of elderly male population under current healm care program
Received:April 07, 2010  Revised:September 12, 2012
DOI:10.3760/cma.j.issn.0254-6450.2010.10.021
KeyWord: 缺血性心脑血管病  老年人群  预测模型
English Key Word: Ischemic cardiovascular disease  Aged population  Prediction model
FundProject:中央保健科研课题(06H050);国家科技支撑计划(2009BAl86801);军队“十一五”课题(06L037);首都医学发展基金莺点项目(2007-2039)
Author NameAffiliationE-mail
CHEN Jin-hong The General Hospital of CAPF Beijing 100039, China
The General Hospital of PLA 
yhe301@sina.com; cjh007@126.Com 
WU Hai-yun The General Hospital of PLA  
HE Kun-lun The General Hospital of PLA  
HE Yao The General Hospital of PLA  
QIN Yin-he The General Hospital of PLA  
Hits: 2770
Download times: 1617
Abstract:
      目的 建立和验证老年人群缺血性心脑血管病(ICVD)预测模型。方法 统计分析 来自某保健医院2003年5月的体检资料、历年住院资料、问卷调企资料和电话同访资料。按照4:1 的比例随机抽取基线人群,生成建模组和验证组。将验证人群基线资料代入建模人群的回门模型 生成预测值。用ROC曲线下面积(AUC)检验预测模霉!!的判别能力;用Hosmer-Lemeshow检验比 较预测率每十分位分组的平均值和实际率来判断预测的准确性;将预测的6年ICVD发病风险的 人群均值与实际观察到的6年累计患病率进行比较,计算误差率,验证预测模型群体水平的预测 能力。结果 分析样本为2271名>65岁男性老年人,建模人群1817人,验证人群454人。把年龄 分为两层(≥75岁高龄组;<75岁老龄组)建立分层Cox比例风险回归模型。老龄组有统计学意 义的危险|天1素是年龄、SBP、血清肌酐(Scr)、空腹血糖(FBG),保护因素是高密度脂蛋白胆固醇 (HDL.C);高龄组有统计学意义的危险冈素是BMI、SBP、TC、Scr、FBG,保护闪素是HDL-C。 ROC的AUC及其95%C/为0.723(0.687.0.759),将个体按预测ICVD累计患病率与实际患病率 进行Hosmer-Lemshow检验:X2=1.43,P=0.786,模型群体水平预测误差率为一2.23%,能力较 好。结论 建立的老年男性人群ICVD预测模型判别能力较好,个体预测能力和群体预测能力较 为满意。
English Abstract:
      objective To establish and verify the prediction model for ischemie cardiovascular disease(ICVD)among the elderly population who were under the current health care programs.Methods Statistical analysis on data from physical examination.hospitalization of the past years.from questionnaire and telephone interview was carried out in May.2003.Data was from a hospital which implementing a health care program.Baseline population with a proportion of 4:1 was randomly selected to generate both module group and verification group.Baseline data was induced to make the veilfication group into regression model of module group and to generate the predictive value.Distinguished ability with area under ROC curve and the predictive veracity were verified through comparing the predictive incidence rate and actual incidence rate of every deciles group by Hosmer-Lemeshow test.Predictive veracity of the prediction model at population level was veilfled through comparing the predictive 6一year incidence rates of ICVD with actual 6一year accumulative incidence rates of ICVD with error rate calculated.Results The samples included 227 l males over the age of 65 with l 8 l 7 people for modeling population and 454 for verified population. All of the samples were stratified into two jayers to establish hierarchical Cox proportional hazard regression model,including one advanced age group(greater than or equal to 75 years old),and another elderly group(1ess than 75 years old).Data from the statically analysis showed that the risk factors in aged group were age。systolic blood pressure,serum creatinine level,fasting blood glucose level,while protective factor was high density lipoprotein;in advanced age group,the risk factors were body weight index,systolic blood pressure,serl.krn total cholesterol level。serum creatinine level.fasting blood glucose level.while protective factor Was HDL-C.The area under the ROC curve (AUC)and 95%Ci were 0.723 and 0.687-0.759 respectively.Discriminating power Was good.A11 individual predictive ICVD cumulative incidenee and actual incidence were analyzed using Hosmer-Lemshow test,X2=1.43,P=0.786,showing that the predictive veracity Was good. Conclusion The stratified COX Hazards Regression model was used to establish prediction model of the aged male population under a certain health care program.The common prediction factor of the two age groups wcre:systolic blood pressure.scrtl//l creatinine 1evel,asting blood glucose level and HDL.C.nlC area under the ROC curve of the verification group Was 0.723,showing that the distinguished ability was good and the predict ability at the individual ievel and at the group level were alSO satisfactory.It Was feasible to using COX Proportional Hazards Regression Model for predicting the population groups.
View Fulltext   Html FullText     View/Add Comment  Download reader
Close