| 孙悦皓,王晓晓,裴敏玥,马心洁,应又又,詹思延,李楠.暴露对结局影响的非随机对照研究偏倚分析工具ROBINS-E（2022）的介绍[J].Chinese journal of Epidemiology,2023,44(9):1454-1461 |
| 暴露对结局影响的非随机对照研究偏倚分析工具ROBINS-E（2022）的介绍 |
| Introduction of a tool to assess Risk of Bias in Non-randomized Studies-of Exposure (2022) |
| Received:February 21, 2023 |
| DOI：10.3760/cma.j.cn112338-20230221-00094 |
| KeyWord: 偏倚风险 评估工具 非随机对照研究 暴露 系统回顾 |
| English Key Word: Bias risk Assessment tool Non-randomized controlled study Exposure Systematic reviews |
| FundProject:国家自然科学基金（81701067） |
| Author Name | Affiliation | E-mail | | Sun Yuehao | Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China | | | Wang Xiaoxiao | Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China | | | Pei Minyue | Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China | | | Ma Xinjie | Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China | | | Ying Youyou | School of Nursing, Peking University, Beijing 100191, China | | | Zhan Siyan | Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China | | | Li Nan | Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China | linan917@163.com |
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| Abstract: |
| 本文介绍了2022年6月最新版非随机对照研究偏倚分析工具ROBINS-E（2022）的内容并举例说明其使用方法。ROBINS-E是一种评估暴露相关非随机对照研究偏倚风险的工具。与ROBINS-E（2019）相比，ROBINS-E（2022）补充了更多适用于观察性研究的偏倚，涵盖的偏倚更加全面，同时增加了针对研究外部真实性的评估。ROBINS-E（2022）增加了初步评估环节，便于提高评估的效率。此外ROBINS-E（2022）使用路径图的形式将信号问题的使用进行了可视化和工具化，使用更加便捷。ROBINS-E（2022）虽然对共暴露的问题有了更多的考虑，但仍然没有解决共暴露中的效应修饰问题，仍有扩展适用的研究范围的空间。 |
| English Abstract: |
| This article introduces the contents of the latest edition Risk of Bias in Non-randomized Studies-of Exposure (ROBINS-E) published in June 2022[ROBINS-E (2022)], and gives some examples about its usage. ROBINS-E is a tool for assessing the risk of bias in non-randomized studies-of exposure. Compared with ROBINS-E (2019), ROBINS-E (2022) adds more bias for observational studies, covers a more comprehensive range of bias, and adds the assessment of the external authenticity of the study. ROBINS-E (2022) adds a preliminary evaluation process to improve the efficiency of evaluation. In addition, ROBINS-E (2022) visualizes and instrumentalizes the use of signal problems in the form of path graph, making it more convenient to use. ROBINS-E (2022), although more consideration has been given to the issue of co-exposure, still does not address the problem of effect modification in co-exposure, and there is still room to expand the applicable research. |
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