Background The use of Mendelian randomization (MR) in epidemiology has increased considerably in recent years, with a subsequent increase in systematic reviews of MR studies. We conducted a systematic review of tools designed for assessing risk of bias and/or quality of evidence in MR studies and a review of systematic reviews of MR studies. Methods We systematically searched MEDLINE, Embase, the Web of Science, preprints servers and Google Scholar for articles containing tools for assessing, conducting and/or reporting MR studies. We also searched for systematic reviews and protocols of systematic reviews of MR studies. From eligible articles we collected data on tool characteristics and content, as well as details of narrative description of bias assessment. Results Our searches retrieved 2464 records to screen, from which 14 tools, 35 systematic reviews and 38 protocols were included in our review. Seven tools were designed for assessing risk of bias/quality of evidence in MR studies and evaluation of their content revealed that all seven tools addressed the three core assumptions of instrumental variable analysis, violation of which can potentially introduce bias in MR analysis estimates. Conclusion We present an overview of tools and methods to assess risk of bias/quality of evidence in MR analysis. Issues commonly addressed relate to the three standard assumptions of instrumental variables analyses, the choice of genetic instrument(s) and features of the population(s) from which the data are collected (particularly in two-sample MR), in addition to more traditional non-MR-specific epidemiological biases. The identified tools should be tested and validated for general use before recommendations can be made on their widespread use. Our findings should raise awareness about the importance of bias related to MR analysis and provide information that is useful for assessment of MR studies in the context of systematic reviews.

中文翻译：

---

评估孟德尔随机研究质量和偏倚风险的工具：系统评价


背景 近年来，孟德尔随机化 (MR) 在流行病学中的应用大幅增加，随后对 MR 研究的系统评价也随之增加。我们对旨在评估 MR 研究中偏倚风险和/或证据质量的工具进行了系统回顾，并对 MR 研究的系统回顾进行了回顾。方法 我们系统地搜索了 MEDLINE、Embase、Web of Science、预印本服务器和 Google Scholar，寻找包含评估、实施和/或报告 MR 研究工具的文章。我们还检索了 MR 研究的系统评价和系统评价方案。我们从符合条件的文章中收集了有关工具特征和内容的数据，以及偏见评估的叙述性描述的详细信息。结果 我们的检索检索到了 2464 条记录进行筛选，其中 14 个工具、35 个系统评价和 38 个方案纳入了我们的评价。设计了七种工具来评估 MR 研究中的偏倚风险/证据质量，对其内容的评估表明，所有七种工具都解决了工具变量分析的三个核心假设，违反这些假设可能会在 MR 分析估计中引入偏差。结论 我们概述了评估 MR 分析中的偏倚风险/证据质量的工具和方法。除了更传统的方法之外，通常解决的问题还涉及工具变量分析的三个标准假设、遗传仪器的选择和收集数据的群体特征（特别是在双样本 MR 中）。非 MR 特异性的流行病学偏差。在就其广泛使用提出建议之前，应对所确定的工具进行测试和验证以供一般使用。 我们的研究结果应该提高人们对 MR 分析相关偏差重要性的认识，并提供有助于在系统评价的背景下评估 MR 研究的信息。