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

Author:

Spiga Francesca12ORCID,Gibson Mark23ORCID,Dawson Sarah1,Tilling Kate12,Davey Smith George12,Munafò Marcus R23,Higgins Julian P T12ORCID

Affiliation:

1. Population Health Sciences, Bristol Medical School, University of Bristol , Bristol, UK

2. Medical Research Council Integrative Epidemiology Unit, University of Bristol , Bristol, UK

3. School of Psychological Science, University of Bristol , Bristol, UK

Abstract

Abstract 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.

Funder

Cancer Research UK

Integrative Cancer Epidemiology Programme

Medical Research Council Integrative Epidemiology Unit

University of Bristol

National Institute for Health Research

NIHR

Bristol Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust

NIHR Applied Research Collaboration

University Hospitals Bristol

Weston NHS Foundation Trust

Publisher

Oxford University Press (OUP)

Subject

General Medicine,Epidemiology

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