Abstract
刘静春,霍亚婷,曹岁霞,王予童,刘卉萌,张彬艳,徐坤,杨佩莹,曾令霞,党少农,颜虹,米白冰.界标分析在队列研究中的应用及实例分析[J].Chinese journal of Epidemiology,2023,44(11):1808-1814
界标分析在队列研究中的应用及实例分析
Application and case study of landmark analysis in cohort study
Received:February 23, 2023  
DOI:10.3760/cma.j.cn112338-20230223-00099
KeyWord: 界标分析  反向因果  队列研究
English Key Word: Landmark analysis  Reverse causation  Cohort study
FundProject:国家自然科学基金(82103944);国家重点研发计划(2017YFC0907200,2017YFC0907201);陕西省科技资源开放共享平台(2023-CX-PT-47)
Author NameAffiliationE-mail
Liu Jingchun Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China 
 
Huo Yating Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China 
 
Cao Suixia Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China 
 
Wang Yutong Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China 
 
Liu Huimeng Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China 
 
Zhang Binyan Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China 
 
Xu Kun Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China 
 
Yang Peiying Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China 
 
Zeng Lingxia Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China 
 
Dang Shaonong Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China 
 
Yan Hong Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China 
 
Mi Baibing Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China 
xjtu.mi@xjtu.edu.cn 
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Abstract:
      队列研究设计具有时序关系明确的特点,其论证因果关联的强度优于其他观察性研究,是分析性流行病学的重要研究方法之一。然而,队列研究对象的纳入过程中常采用筛检诊断或其他方式排除已出现结局事件的个体,而筛检诊断的准确性、排除的有效性会影响纳入研究个体基线状况评估的准确性,进而导致对因果效应的估计可能存在暴露-结局因果倒置。界标分析可以通过排除可能存在暴露-结局时序不明的研究对象以控制反向因果。本研究阐述界标分析的基本原理与分析步骤,并运用中国老年人健康长寿影响因素调查的数据探索体育锻炼与虚弱的关系,展示界标分析的具体应用,以期促进其在队列研究中的应用,从而更准确地推断暴露与结局的因果效应。
English Abstract:
      Cohort study is one of the important research methods in analytical epidemiology because of its clear time sequence relationship, which is better than other observational studies in demonstrating causal association. However, screening diagnosis or other methods are often used to exclude the individuals with outcome events during the enrollment process of the subjects in cohort studies. The accuracy of screening diagnosis and the effectiveness of exclusion will affect the accuracy of the baseline status assessment of the subjects included in the study, which may lead to the causal time sequence reversal of exposure-outcome in the estimation of causal effect. Landmark analysis can be used to control reverse causality by excluding subjects with potentially unknown expose-outcome timing. In this paper, we describe the basic principles and analytical steps of landmark analysis, and use data from the Chinese Longitudinal Healthy Longevity Survey to explore the relationship between physical activity and frailty, and introduce the specific application of landmark analysis for the purpose of facilitating its application and inferring causal effects more accurately in cohort studies.
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