Evidence map›Paper›PMID 30325422›Full record

ArticleInternational journal of epidemiology2019

Contextualizing selection bias in Mendelian randomization: how bad is it likely to be?

Apostolos Gkatzionis, Stephen Burgess

Abstract read
In one paragraph

Article in International journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

113 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. High Blood Pressure and Intraocular Pressure: A Mendelian Randomization Study.Investigative ophthalmology & visual science · 2022
    Pooled it
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  12. Winner's Curse Free Robust Mendelian Randomization with Summary Data.Journal of the American Statistical Association · 2026
    Article
  13. Review
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  16. Article
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53 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Apostolos GkatzionisMRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Stephen BurgessMRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.

Funding

British Heart Foundation RG/13/13/30194Medical Research Council MC_UU_00002/7Medical Research Council MR/L003120/1Medical Research Council MR/N027493/1Medical Research Council RG88311Wellcome TrustWellcome Trust 204623/Z/16/Z
6 · The paper itself

Abstract

backgroundSelection bias affects Mendelian randomization investigations when selection into the study sample depends on a collider between the genetic variant and confounders of the risk factor-outcome association. However, the relative importance of selection bias for Mendelian randomization compared with other potential biases is unclear.

methodsWe performed an extensive simulation study to assess the impact of selection bias on a typical Mendelian randomization investigation. We considered inverse probability weighting as a potential method for reducing selection bias. Finally, we investigated whether selection bias may explain a recently reported finding that lipoprotein(a) is not a causal risk factor for cardiovascular mortality in individuals with previous coronary heart disease.

resultsSelection bias had a severe impact on bias and Type 1 error rates in our simulation study, but only when selection effects were large. For moderate effects of the risk factor on selection, bias was generally small and Type 1 error rate inflation was not considerable. Inverse probability weighting ameliorated bias when the selection model was correctly specified, but increased bias when selection bias was moderate and the model was misspecified. In the example of lipoprotein(a), strong genetic associations and strong confounder effects on selection mean the reported null effect on cardiovascular mortality could plausibly be explained by selection bias.

conclusionsSelection bias can adversely affect Mendelian randomization investigations, but its impact is likely to be less than other biases. Selection bias is substantial when the effects of the risk factor and confounders on selection are particularly large.

Indexed as

Mendelian Randomization AnalysisSelection BiasCardiovascular DiseasesCausalityComputer SimulationConfounding Factors, EpidemiologicCoronary DiseaseHumansLipoprotein(a)Risk FactorsLipoprotein(a)causal inferencecollider biasinstrumental variablesinverse probability weightingselection bias

Identifiers

PMID30325422
PMCPMC6659463

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.