Evidence map›Paper›PMID 37712381›Full record

ArticleJournal of global health2023

Understanding and reporting odds ratios as rate-ratio estimates in case-control studies.

Steven Kerr, Sander Greenland, Karen Jeffrey, Tristan Millington, Stuart Bedston, Lewis Ritchie, Colin R Simpson, Adeniyi Francis Fagbamigbe, Amanj Kurdi, Chris Robertson and 2 more

Abstract read
In one paragraph

Article in Journal of global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. 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

12 authors.

Steven Kerr *Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, Scotland, UK.
Sander Greenland *Department of Epidemiology and Department of Statistics, University of California, Los Angeles, California, USA.
Karen JeffreyCentre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, Scotland, UK.
Tristan MillingtonCentre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, Scotland, UK.
Stuart BedstonPopulation Data Science, Swansea University Medical School, Swansea, Wales, UK.
Lewis RitchieAcademic Primary Care, University of Aberdeen School of Medicine and Dentistry, Aberdeen, Scotland, UK.
Colin R SimpsonWellington Faculty of Health, Victoria University of Wellington, Wellington, NZ.
Adeniyi Francis FagbamigbeInstitute of Applied Health Sciences, University of Aberdeen School of Medicine and Dentistry, Aberdeen, Scotland, UK.
Amanj KurdiStrathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, Scotland, UK.
Chris RobertsonDepartment of Mathematics and Statistics, University of Strathclyde, Glasgow, Scotland.
Aziz SheikhCentre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, Scotland, UK.
Igor RudanCentre for Global Health, Usher Institute, The University of Edinburgh, Edinburgh, Scotland, UK.

Funding

Medical Research Council MC_PC_19075Medical Research Council MC_PC_20058
6 · The paper itself

Abstract

Background: We noted that there remains some confusion in the health-science literature on reporting sample odds ratios as estimated rate ratios in case-control studies. Methods: We recap historical literature that definitively answered the question of when sample odds ratios (ORs) from a case-control study are consistent estimators for population rate ratios. We use numerical examples to illustrate the magnitude of the disparity between sample ORs in a case-control study and population rate ratios when sufficient conditions for them to be equal are not satisfied. Results: We stress that in a case-control study, sampling controls from those still at risk at the time of outcome event of the index case is not sufficient for a sample OR to be a consistent estimator for an intelligible rate ratio. In such studies, constancy of the exposure prevalence together with constancy of the hazard ratio (HR) (i.e., the instantaneous rate ratio) over time is sufficient for this result if sampling time is not controlled; if time is controlled, constancy of the HR will suffice. We present numerical examples to illustrate how failure to satisfy these conditions adds a small systematic error to sample ORs as estimates of population rate ratios. Conclusions: We recommend that researchers understand and critically evaluate all conditions used to interpret their estimates as consistent for a population parameter in case-control studies.

Indexed as

Research PersonnelCase-Control StudiesHumansOdds Ratio

Identifiers

PMID37712381
PMCPMC10502767

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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.