Estimating relative risks and risk differences in randomised controlled trials: a systematic review of current practice.

Jacqueline Thompson, Samuel I Watson, Lee Middleton, Karla Hemming

Abstract readSystematic Review

In one paragraph

Synthesis in Trials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Protocol for a review of statistical methods used to estimate risk ratios and risk differences in parallel cluster randomised trials.Trials · 2026
Article

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

4 authors.

Jacqueline ThompsonDepartment of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Edgbaston, West Midlands, B15 2TT, UK. J.Y.Thompson@bham.ac.uk.

Samuel I WatsonDepartment of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Edgbaston, West Midlands, B15 2TT, UK.

Lee MiddletonDepartment of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Edgbaston, West Midlands, B15 2TT, UK.

Karla HemmingDepartment of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Edgbaston, West Midlands, B15 2TT, UK.

Funding

Medical Research Council MR/V038591/1

6 · The paper itself

Abstract

backgroundGuidelines for randomised controlled trials (RCTs) recommend reporting relative and absolute measures of effect for binary outcomes while adjusting for covariates. There are a number of different ways covariate-adjusted relative risks and risk differences can be estimated.

objectivesOur goal was to identify methods used to estimate covariate-adjusted relative risk and risk differences in RCTs published in high-impact journals with binary outcomes. Other secondary objectives included the identification of how covariates are chosen for adjustment and whether covariate adjustment results in an increase in statistical precision in practice.

methodsWe included two-arm parallel RCTs published in JAMA, NEJM, Lancet, or the BMJ between January 1, 2018, and March 11, 2023, reporting relative risks or risk differences as a summary measure for a binary primary outcome. The search was conducted in Ovid-MEDLINE.

resultsOf the 308 RCTs identified, around half (49%; 95% CI: 43-54%) reported a covariate-adjusted relative risk or risk difference. Of these, 82 reported an adjusted relative risk. When the reporting was clear (n = 65, 79%), the log-binomial model (used in 65% of studies; 95% CI: 52-76%) and modified Poisson (29%; 95% CI: 19-42%) were most commonly used. Of the 92 studies that reported an adjusted risk difference, when the reporting was clear (n = 56, 61%), the binomial model (used in 48% of studies; 95% CI: 35-62%) and marginal standardisation (21%; 95% CI: 12-35%) were the common approaches used.

conclusionsApproximately half of the RCTs report either a covariate-adjusted relative risk or risk difference. Many RCTs lack adequate details on the methods used to estimate covariate-adjusted effects. Of those that do report the approaches used, the binomial model, modified Poisson and to a lesser extent marginal standardisation are the approaches used.

Indexed as

Randomized Controlled Trials as TopicData Interpretation, StatisticalHumansResearch DesignRisk AssessmentRisk FactorsBinary outcomesCovariate adjustmentRelative riskRisk differenceStatistical efficiencyStatistical practice

Identifiers

PMID39748241

DOI10.1186/s13063-024-08690-w

PMCPMC11694472

What Socratic holds

Textmetadata

LicenceCC BY

Read underepoch 390

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 Socratic graph.