Deng S W, Zhao H Y, Zhan S Y
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.
School of Medicine, Chongqing University, Chongqing 400030, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2024 Sep 10;45(9):1273-1282. doi: 10.3760/cma.j.cn112338-20240123-00037.
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. 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. 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. 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.
总结近年来发表的涉及糖尿病患者的药物流行病学研究在研究设计和分析方面的特征，并建立药物流行病学研究中与时间相关偏倚的识别流程。使用PubMed、Embase、中国知网和万方对2012年1月1日至2022年9月26日期间发表的相关研究论文进行系统的文献检索。由两名审稿人独立进行文献筛选和数据提取。根据不同与时间相关偏倚的机制以及纳入研究论文在研究设计和分析方法方面的特征，制定了所有类型与时间相关偏倚的识别流程。共纳入281篇研究论文，其中58篇（20.64%）特别提到了研究中考虑的某些与时间相关的偏倚。基于范围综述结果，总结了识别与时间相关偏倚的要点，涉及药物流行病学研究中与时间相关偏倚识别流程中的数据源、研究设计、对照选择、对照药物、糖尿病病程匹配、洗脱期识别、诱导/潜伏期识别、随访起始识别、时间窗识别、统计分析方法、敏感性分析以及其他设计和分析要素。与时间相关的偏倚在药物流行病学研究中很常见，可能会显著影响研究结果。基于范围综述结果，本研究进一步制定了药物流行病学研究中与时间相关偏倚的识别流程，这将有助于研究人员识别和避免与时间相关的偏倚，提高药物流行病学研究中相关证据的可靠性。
