Evidence map›Paper›PMID 39030722›Full record

ArticleAmerican journal of epidemiology2025

Overcoming time-varying confounding in self-controlled case series with active comparators: application and recommendations.

Anna Schultze, Jeremy Brown, John Logie, Marianne Cunnington, Gema Requena, Iain A Gillespie, Stephen J W Evans, Ian Douglas, Nicholas Galwey

Abstract read
In one paragraph

Article in American journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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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

9 authors.

Anna SchultzeDepartment of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom.ORCID 0000-0002-1637-837X
Jeremy BrownDepartment of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom.ORCID 0000-0002-9941-7759
John LogieGlaxoSmithKline PLC, London WC1A 1DG, United Kingdom.ORCID 0009-0005-4707-6939
Marianne CunningtonGlaxoSmithKline PLC, London WC1A 1DG, United Kingdom.ORCID 0009-0002-2398-2281
Gema RequenaGlaxoSmithKline PLC, London WC1A 1DG, United Kingdom.ORCID 0000-0002-1889-6656
Iain A GillespieGlaxoSmithKline PLC, London WC1A 1DG, United Kingdom.ORCID 0000-0002-2265-9506
Stephen J W EvansDepartment of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom.ORCID 0000-0002-1474-2596
Ian DouglasDepartment of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom.ORCID 0000-0002-8970-1406
Nicholas GalweyGlaxoSmithKline PLC, London WC1A 1DG, United Kingdom.ORCID 0000-0002-2110-3194

Funding

GlaxoSmithKline
6 · The paper itself

Abstract

Confounding by indication is a key challenge for pharmacoepidemiologists. Although self-controlled study designs address time-invariant confounding, indications sometimes vary over time. For example, infection might act as a time-varying confounder in a study of antibiotics and uveitis, because it is time-limited and a direct cause of both receipt of antibiotics and uveitis. Methods for incorporating active comparators in self-controlled studies to address such time-varying confounding by indication have only recently been developed. In this paper, we formalize these methods and provide a detailed description for how the active comparator rate ratio can be derived in a self-controlled case series: either by explicitly comparing the regression coefficients for a drug of interest and an active comparator under certain circumstances using a simple ratio approach or through the use of a nested regression model. The approaches are compared in 2 case studies, one examining the association between thiazolidinedione use and fractures and one examining the association between fluoroquinolone use and uveitis, using the United Kingdom's Clinical Practice Research Datalink. Finally, we provide recommendations for the use of these methods, which we hope will support the design, execution, and interpretation of self-controlled case series using active comparators and thereby increase the robustness of pharmacoepidemiologic studies. This article is part of a Special Collection on Pharmacoepidemiology.

Indexed as

PharmacoepidemiologyAnti-Bacterial AgentsConfounding Factors, EpidemiologicFluoroquinolonesHumansRegression AnalysisResearch DesignThiazolidinedionesTime FactorsUnited KingdomUveitisAnti-Bacterial AgentsFluoroquinolonesThiazolidinedionesClinical Practice Research Datalinkfluoroquinolonesself-controlled case seriesthiazolidinedionesunmeasured confounding

Identifiers

PMID39030722
PMCPMC11735952

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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.