Causal factors in primary open angle glaucoma: a phenome-wide Mendelian randomisation study

Julian, Thomas; Girach, Zain; Sanderson, Eleanor; Guo, Hui; Yu, Jonathan; Cooper‐Knock, Johnathan; Black, Graeme; Sergouniotis, Panagiotis I.

doi:10.1101/2022.10.30.22281718

Cited by 1 publication

(1 citation statement)

References 59 publications

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“… 20 Markozannes 99 planned to use a self-developed tool based on the results of the main analysis and of the sensitivity analysis; Naassila 100–102 planned to use Q-GENIE; 25 Shi 105 , 106 planned to use a modified version of a recently developed tool (no reference provided); Visontay 112 , 113 planned to use the tool developed by Mamluk; 28 and Wong 115 planned to conduct risk-of-bias assessment based on the guidelines from Davies. 21 Of the seven protocols describing a MR-specific risk-of-bias/quality-of-evidence assessment without using a structured tool, four planned an assessment based on the literature: Grover, 80 , 81 Jiang 86 and van Oort 111 referred to the MR methods protocol published by Grover 27 and Julian 87 did not report any reference. Of the remaining four protocols, Saribaz 104 planned to develop a risk-of-bias assessment method at the time of conducting the review; M Lee 93 planned to perform a descriptive assessment of the MR methods and of the genetic variants used in included studies; Luo 96 planned to perform an assessment based on sensitivity analysis methods and different choices of genetic variants as instrumental variables; Treur 110 planned to perform an assessment based on sensitivity analysis methods, on the choice of genetic variants, on the presence of sample overlap (two-sample MR studies) and on the use of sensitivity analyses.…”

Section: Resultsmentioning

confidence: 99%

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

Spiga

Gibson

Dawson

et al. 2022

International Journal of Epidemiology

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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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