ArticleJournal of clinical epidemiology2015
Relative risk reduction is useful metric to standardize effect size for public heath interventions for translational research.
Article in Journal of clinical epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- Effect of genetics clinical decision support tools on health-care providers' decision making: a mixed-methods systematic review.Genetics in medicine : official journal of the American College of Medical Genetics · 2021Pooled it
- Pooled it
- Changes in Cardiovascular Health, Genetic Risk, and Cardiometabolic Diseases: Evidence From a Large-Scale Cohort Study.Journal of the American Heart Association · 2025Article
- Best (but oft-forgotten) practices: expressing and interpreting associations and effect sizes in clinical outcome assessments.The American journal of clinical nutrition · 2016Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
objectivesHeterogeneity of effect measures in intervention studies undermines the use of evidence to inform policy. Our objective was to develop a comprehensive algorithm to convert all types of effect measures to one standard metric, relative risk reduction (RRR). STUDY DESIGN AND
settingThis work was conducted to facilitate synthesis of published intervention effects for our epidemic modeling of the health impact of human immunodeficiency virus [HIV testing and counseling (HTC)]. We designed and implemented an algorithm to transform varied effect measures to RRR, representing the proportionate reduction in undesirable outcomes.
resultsOur extraction of 55 HTC studies identified 473 effect measures representing unique combinations of intervention-outcome-population characteristics, using five outcome metrics: pre-post proportion (70.6%), odds ratio (14.0%), mean difference (10.2%), risk ratio (4.4%), and RRR (0.9%). Outcomes were expressed as both desirable (29.5%, eg, consistent condom use) and undesirable (70.5%, eg, inconsistent condom use). Using four examples, we demonstrate our algorithm for converting varied effect measures to RRR and provide the conceptual basis for advantages of RRR over other metrics.
conclusionOur review of the literature suggests that RRR, an easily understood and useful metric to convey risk reduction associated with an intervention, is underused by original and review studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.