4.7 Review

Tools for assessing quality and risk of bias in Mendelian randomization studies: a systematic review

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/ije/dyac149

关键词

Mendelian randomization; genetic instrument; bias; tool; guideline; risk-of-bias assessment

资金

  1. Cancer Research UK programme grant (the Integrative Cancer Epidemiology Programme) [C18281/A29019]
  2. Medical Research Council Integrative Epidemiology Unit (MRC IEU) at the University of Bristol [MC_UU_00011/1, MM_UU_00011/3, MM_UU_00011/7]
  3. National Institute for Health Research (NIHR) [NF-SI-0617-10145]
  4. NIHR Bristol Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust
  5. University of Bristol
  6. NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust

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This study conducted a systematic review of tools designed for assessing risk of bias and/or quality of evidence in Mendelian randomization (MR) studies. The review identified seven tools specifically designed for assessing bias and quality of evidence in MR studies, all of which addressed the core assumptions of instrumental variable analysis.
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.

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