| 邓思危,赵厚宇,詹思延.基于概况性综述的药物流行病学研究中时间相关性偏倚识别流程[J].Chinese journal of Epidemiology,2024,45(9):1273-1282 |
| 基于概况性综述的药物流行病学研究中时间相关性偏倚识别流程 |
| Identification process of time-related bias in pharmacoepidemiologic research based on a scoping review |
| Received:January 23, 2024 |
| DOI：10.3760/cma.j.cn112338-20240123-00037 |
| KeyWord: 时间相关性偏倚 药物流行病学 概况性综述 偏倚识别流程 |
| English Key Word: Time-related bias Pharmacoepidemiology Scoping review Bias identification process |
| FundProject:国家自然科学基金（81973146，82204157）；国家自然科学基金重点项目（82330107） |
| Author Name | Affiliation | | Deng Siwei | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Institute for Artificial Intelligence, Peking University, Beijing 100871, China
Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China | | Zhao Houyu | School of Medicine, Chongqing University, Chongqing 400030, China | | Zhan Siyan | Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Institute for Artificial Intelligence, Peking University, Beijing 100871, China
Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China |
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| Abstract: |
| 目的 总结近年来发表的以糖尿病患者为基础人群的药物流行病学研究在设计和分析上的各项特征，梳理出药物流行病学研究中时间相关性偏倚的识别流程。方法 系统检索PubMed、Embase、中国知网和万方数据知识服务平台等中英文数据库，发表时间限定为2012年1月1日至2022年9月26日。双人独立筛选文献、提取信息，然后结合各类时间相关性偏倚的产生机制和纳入文献在研究设计、分析方法等方面的特征，构建针对不同种类时间相关性偏倚的识别流程。结果 共纳入文献281篇，其中58篇（20.64%）文献明确提及研究关注了哪些时间相关性偏倚。在概况性综述结果的基础上，研究总结归纳了识别时间相关性偏倚的关键问题，涉及数据来源、研究类型、对照类型、对比药物、病程匹配情况、洗脱期设置、诱导期/潜伏期设置、随访起点、暴露时间窗设置、统计分析方法、敏感性分析等设计及分析要素，构成了药物流行病学研究中时间相关性偏倚的识别流程。结论 药物流行病学研究中时间相关性偏倚普遍存在且可能对结果产生重要影响。本研究在概况性综述结果的基础上，进一步梳理出了药物流行病学研究中时间相关性偏倚的识别流程，将有利于研究者在开展药物流行病学研究时识别并规避时间相关性偏倚，提高相关证据的可靠性。 |
| English Abstract: |
| Objective To summarize the characteristics of pharmacoepidemiologic research involving diabetes patients, which were published in recent years, in terms of study design and analysis, and develop an identification process for time-related biases in pharmacoepidemiologic research. Methods PubMed, Embase, CNKI and Wanfang were used for a systematical literature retrieval of relevant study papers published between January 1,2012 and September 26, 2022. Literature screening and data extraction were performed independently by two reviewers. Based on the mechanisms of different time-related biases and the characteristics of included study papers in terms of study design and analysis methods, an identification process for all types of time-related biases was developed. Results A total of 281 study papers were included, of which 58 (20.64%) specifically mentioned certain time-related biases considered in the study. Based on the scoping review results, key points to identify time-related biases were summarized, involving data source, study design, control selection, comparator drugs, matching the duration of diabetes, identification of the washout period, identification of the induction/latency period, identification of the initiation of follow-up, identification of time window, statistical analysis methods, sensitivity analysis, and other design and analytical elements, in the identification process for time-related biases in pharmacoepidemiologic research. Conclusions Time-related biases are common in pharmacoepidemiologic research and might significantly impact the study results. Based on scoping review results, this study further developed an identification process for time-related biases in pharmacoepidemiologic research, which will help researchers identify and avoid time-related biases and improve the reliability of related evidence in pharmacoepidemiologic research. |
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