Evidence map›Paper›PMID 42475504›Full record

ArticleInternational journal of epidemiology2026

Survival as a source of confounding, selection bias, and effect modification.

C Mary Schooling, Guoyi Yang

Abstract read
In one paragraph

Article in International journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

C Mary SchoolingGraduate School of Public Health and Health Policy, City University of New York, New York, NY, United States.ORCID 0000-0001-9933-5887
Guoyi YangSchool of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.ORCID 0000-0002-4387-386X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurvival is a long-standing source of confounding, selection bias, and effect modification that is often overlooked. Here, we describe how it can occur and when it can be averted.

methodsDirected acyclic graphs were used to illustrate how survival could cause confounding and selection bias. Selection diagrams were used to illustrate how survival could cause effect modification by factors such as age or health status.

resultsSurvival can be a confounder that biases towards favouring the exposure when exposure allocation starts or changes after recruitment. Survival can be a source of Type 1 selection bias that attenuates or reverses estimates when the exposure and outcome, or the exposure and a competing risk of the outcome, affect survival before recruitment. Confounding and selection bias by survival can largely be averted by ensuring exposure allocation coincides with recruitment. Given survival is usually most relevant to older or sicker people, confounding and selection bias due to survival are likely more evident with advancing age or poorer health status.

conclusionsConfounding by survival should be considered when exposure allocation starts or changes after recruitment. Type 1 selection bias from survival should be considered when the exposure starts before recruitment. Given that long-term exposures are often of interest, and confounding as well as selection bias are difficult to address, study designs less open to these biases might be preferable.

Indexed as

Selection BiasConfounding Factors, EpidemiologicEffect Modifier, EpidemiologicHumansSurvival Analysisconfoundingeffect modificationselection biasselection diagramssurvival

Identifiers

PMID42475504
PMCPMC13384058

What OpenQuestion holds

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LicenceCC BY-NC
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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.