Development of a prediction model to identify undiagnosed chronic obstructive pulmonary disease patients in primary care settings in China  

作　　者：Buyu Zhang Dong Sun Hongtao Niu Fen Dong Jun Lyu Yu Guo Huaidong Du Yalin Chen Junshi Chen Weihua Cao Ting Yang Canqing Yu Zhengming Chen Liming Li on behalf of the China Kadoorie Biobank Collaborative Group 

机构地区：[1]Department of Epidemiology and Biostatistics,School of Public Health,Peking University,Beijing 100191,China [2]Department of Pulmonary and Critical Care Medicine,Center of Respiratory Medicine,China–Japan Friendship Hospital,Beijing 100029,China [3]National Center for Respiratory Medicine and National Clinical Research Center for Respiratory Diseases,Beijing 100029,China [4]Institute of Respiratory Medicine,Chinese Academy of Medical Sciences,Beijing 100007,China [5]Peking University Center for Public Health and Epidemic Preparedness and Response,Beijing 100191,China [6]Key Laboratory of Molecular Cardiovascular Sciences(Peking University),Ministry of Education,Beijing 100191,China [7]National Center for Cardiovascular Diseases,Fuwai Hospital,Chinese Academy of Medical Sciences,Beijing 100037,China [8]Medical Research Council Population Health Research Unit at the University of Oxford,Oxford OX37LF,UK [9]Clinical Trial Service Unit and Epidemiological Studies Unit,Nuffield Department of Population Health,University of Oxford,Oxford OX37LF,UK [10]Maiji Center for Disease Control and Prevention,Tianshui,Gansu 741020,China [11]China National Center for Food Safety Risk Assessment,Beijing 100022,China [12]不详

出　　处：《Chinese Medical Journal》2023年第6期676-682,共7页中华医学杂志（英文版）

基　　金：supported by the National Key Research&Development Program of China(Nos.2016YFC1303904 and 2016YFC0900500);National Natural Science Foundation of China(Nos.81941018,91846303,and 91843302)

摘　　要：Background:At present,a large number of chronic obstructive pulmonary disease(COPD)patients are undiagnosed in China.Thus,this study aimed to develop a simple prediction model as a screening tool to identify patients at risk for COPD.Methods:The study was based on the data of 22,943 subjects aged 30 to 79 years and enrolled in the second resurvey of China Kadoorie Biobank during 2012 and 2013 in China.We stepwisely selected the predictors using logistic regression model.Then we tested the model validity through P-P graph,area under the receiver operating characteristic curve(AUROC),ten-fold cross validation and an external validation in a sample of 3492 individuals from the Enjoying Breathing Program in China.Results:The final prediction model involved 14 independent variables,including age,sex,location(urban/rural),region,educational background,smoking status,smoking amount(pack-years),years of exposure to air pollution by cooking fuel,family history of COPD,history of tuberculosis,body mass index,shortness of breath,sputum and wheeze.The model showed an area under curve(AUC)of 0.72(95%confidence interval[CI]:0.72-0.73)for detecting undiagnosed COPD patients,with the cutoff of predicted probability of COPD=0.22,presenting a sensitivity of 70.13%and a specificity of 62.25%.The AUROC value for screening undiagnosed patients with clinically significant COPD was 0.68(95%CI:0.66-0.69).Moreover,the ten-fold cross validation reported an AUC of 0.72(95%CI:0.71-0.73),and the external validation presented an AUC of 0.69(95%CI:0.68-0.71).Conclusion:This prediction model can serve as a first-stage screening tool for undiagnosed COPD patients in primary care settings.

关 键 词：Chronic obstructive pulmonary disease SCREENING Prediction model China Kadoorie Biobank 

分 类 号：R563.9[医药卫生—呼吸系统]