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

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。

Introduction of a tool to assess Risk of Bias in Non-randomized Studies-of Exposure (2022)

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.