Evidence map›Paper›PMID 30854785›Full record

ArticleResearch synthesis methods2019

Pitfalls of using the risk ratio in meta-analysis.

Ilyas Bakbergenuly, David C Hoaglin, Elena Kulinskaya

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Research synthesis methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 20 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 20 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

39 citing papers in PubMed, 20 syntheses or guidelines pooled it.

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  20. Estimation in meta-analyses of response ratios.BMC medical research methodology · 2020
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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

3 authors.

Ilyas BakbergenulySchool of Computing Sciences, University of East Anglia, Norwich, United Kingdom.ORCID https://orcid.org/0000-0001-7792-9051
David C HoaglinUniversity of Massachusetts Medical School, Worcester, Massachusetts.ORCID https://orcid.org/0000-0003-1336-181X
Elena KulinskayaSchool of Computing Sciences, University of East Anglia, Norwich, United Kingdom.

Funding

Economic and Social Research Council ES/L011859/1
6 · The paper itself

Abstract

For meta-analysis of studies that report outcomes as binomial proportions, the most popular measure of effect is the odds ratio (OR), usually analyzed as log(OR). Many meta-analyses use the risk ratio (RR) and its logarithm because of its simpler interpretation. Although log(OR) and log(RR) are both unbounded, use of log(RR) must ensure that estimates are compatible with study-level event rates in the interval (0, 1). These complications pose a particular challenge for random-effects models, both in applications and in generating data for simulations. As background, we review the conventional random-effects model and then binomial generalized linear mixed models (GLMMs) with the logit link function, which do not have these complications. We then focus on log-binomial models and explore implications of using them; theoretical calculations and simulation show evidence of biases. The main competitors to the binomial GLMMs use the beta-binomial (BB) distribution, either in BB regression or by maximizing a BB likelihood; a simulation produces mixed results. Two examples and an examination of Cochrane meta-analyses that used RR suggest bias in the results from the conventional inverse-variance-weighted approach. Finally, we comment on other measures of effect that have range restrictions, including risk difference, and outline further research.

Indexed as

Meta-Analysis as TopicRiskAlgorithmsAntidepressive Agents, TricyclicComputer SimulationDepressionDiureticsFemaleHumansLikelihood FunctionsLinear ModelsOdds RatioPre-EclampsiaPregnancyRegression AnalysisRisk AssessmentAntidepressive Agents, TricyclicDiureticsbeta-binomial modellog-binomial modelrelative riskresponse ratiorisk difference

Identifiers

PMID30854785
PMCPMC6767076

What OpenQuestion holds

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LicenceCC BY
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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.