Evidence map›Paper›PMID 25304503›Full record

ArticleJournal of clinical epidemiology2015

Predictive distributions were developed for the extent of heterogeneity in meta-analyses of continuous outcome data.

Kirsty M Rhodes, Rebecca M Turner, Julian P T Higgins

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

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 186 papers, 73 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
186citing papers in PubMed, 73 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

186 citing papers in PubMed, 73 syntheses or guidelines pooled it.

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  19. Systematic review and meta-analysis of preoperative predictors for early mortality following hip fracture surgery.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
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126 more citing papers are in PubMed but not listed here.

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.

Kirsty M RhodesMRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK. Electronic address: kirsty.rhodes@mrc-bsu.cam.ac.uk.
Rebecca M TurnerMRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.
Julian P T HigginsSchool of Social and Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK; Centre for Reviews and Dissemination, A/B Block, Alcuin College, University of York, York, YO10 5DD, UK.

Funding

Medical Research Council MC_U105260558Medical Research Council MC_U105285807Medical Research Council MR/K025643/1Medical Research Council U105260558
6 · The paper itself

Abstract

objectivesEstimation of between-study heterogeneity is problematic in small meta-analyses. Bayesian meta-analysis is beneficial because it allows incorporation of external evidence on heterogeneity. To facilitate this, we provide empirical evidence on the likely heterogeneity between studies in meta-analyses relating to specific research settings. STUDY DESIGN AND

settingOur analyses included 6,492 continuous-outcome meta-analyses within the Cochrane Database of Systematic Reviews. We investigated the influence of meta-analysis settings on heterogeneity by modeling study data from all meta-analyses on the standardized mean difference scale. Meta-analysis setting was described according to outcome type, intervention comparison type, and medical area. Predictive distributions for between-study variance expected in future meta-analyses were obtained, which can be used directly as informative priors.

resultsAmong outcome types, heterogeneity was found to be lowest in meta-analyses of obstetric outcomes. Among intervention comparison types, heterogeneity was lowest in meta-analyses comparing two pharmacologic interventions. Predictive distributions are reported for different settings. In two example meta-analyses, incorporating external evidence led to a more precise heterogeneity estimate.

conclusionHeterogeneity was influenced by meta-analysis characteristics. Informative priors for between-study variance were derived for each specific setting. Our analyses thus assist the incorporation of realistic prior information into meta-analyses including few studies.

Indexed as

Bayes TheoremData Interpretation, StatisticalMeta-Analysis as TopicDatabases, FactualFemaleHumansMarkov ChainsObstetricsPregnancyResearch DesignBayesian analysisContinuous dataHeterogeneityIntervention studiesMeta-analysisStandardized mean difference

Identifiers

PMID25304503
PMCPMC4270451

What OpenQuestion holds

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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.