Cited by 838Meta-analysis and systematic reviewsDelphi Technique in ResearchStatistical Methods in Epidemiology

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Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

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Turner, Rebecca M, Davey, Jonathan, Clarke, Mike J, Thompson, Simon G, Higgins, Julian PT·2012·International Journal of Epidemiology

DOI 10.1093/ije/dys041PMC PMC3396310

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Abstract

BACKGROUND: Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care. METHODS: Our analyses included 14 886 meta-analyses from the Cochrane Database of Systematic Reviews. We classified each meta-analysis according to the type of outcome, type of intervention comparison and medical specialty. By modelling the study data from all meta-analyses simultaneously, using the log odds ratio scale, we investigated the impact of meta-analysis characteristics on the underlying between-study heterogeneity variance. Predictive distributions were obtained for the heterogeneity expected in future meta-analyses. RESULTS: Between-study heterogeneity variances for meta-analyses in which the outcome was all-cause mortality were found to be on average 17% (95% CI 10-26) of variances for other outcomes. In meta-analyses comparing two active pharmacological interventions, heterogeneity was on average 75% (95% CI 58-95) of variances for non-pharmacological interventions. Meta-analysis size was found to have only a small effect on heterogeneity. Predictive distributions are presented for nine different settings, defined by type of outcome and type of intervention comparison. For example, for a planned meta-analysis comparing a pharmacological intervention against placebo or control with a subjectively measured outcome, the predictive distribution for heterogeneity is a log-normal (-2.13, 1.58(2)) distribution, which has a median value of 0.12. In an example of meta-analysis of six studies, incorporating external evidence led to a smaller heterogeneity estimate and a narrower confidence interval for the combined intervention effect. CONCLUSIONS: Meta-analysis characteristics were strongly associated with the degree of between-study heterogeneity, and predictive distributions for heterogeneity differed substantially across settings. The informative priors provided will be very beneficial in future meta-analyses including few studies.

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Figure 1 Distribution of non-zero estimates for between-study heterogeneity variance (), plotted on log scaleCC BY-NC · PubMed Central

Figure 2 Predictive distributions for heterogeneity variance (plotted on log scale) in: (a) pharmacological vs placebo/control meta-analysis measuring all-cause mortality; (b) non-pharmacological meta-analysis measuring a subjective outcomeCC BY-NC · PubMed Central

Figure 3 Conventional random-effects meta-analysis combining results from six studies on the effectiveness of granulocyte (white blood cell) transfusions for prevention of mortality in patients with neutropenia or neutrophil dysfunction16CC BY-NC · PubMed Central

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Authors: Turner, R. M., Davey, J., Clarke, M. J., Thompson, S. G., & Higgins, J. P.
Affiliations: MRC Biostatistics Unit (GB)
Queen's University Belfast (GB)
Corresponding author: Turner, Rebecca M
ORCID: Turner, Rebecca M
Clarke, Mike J
Thompson, Simon G
Higgins, Julian PT
Venue: International Journal of Epidemiology
Publisher: Oxford University Press (OUP)
Published: 2012-03-29
Volume: 41
Issue: 3
Pages: 818-827
ISSN: 0300-5771 (ISSN-L)
1464-3685
DOI: 10.1093/ije/dys041
PMC: PMC3396310
OpenAlex: W2131701504
Cited by: 837
References: 24
Citations by year: 2026: 53 · 2025: 49 · 2024: 59 · 2023: 76 · 2022: 71 · 2021: 103 · 2020: 98 · 2019: 60 · 2018: 67 · 2017: 61 · 2016: 56 · 2015: 37 · 2014: 32 · 2013: 11 · 2012: 2
FWCI: 7.31
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc
Locations: International Journal of Epidemiology (publishedVersion, cc-by-nc)
Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
PubMed Central (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
UCL Discovery (University College London) (submittedVersion)
HighWire Press Open Archive (submittedVersion)
Explore Bristol Research (submittedVersion)
Funders: British Heart Foundation (RG/08/014/24067)
Medical Research Council (U1052.00.011)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Social Sciences › Sociology and Political Science › Delphi Technique in Research
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: study heterogeneity, Bayesian meta-analysis, informative priors, external evidence, predictive distribution, Cochrane Database of Systematic Reviews, pharmacological interventions, all-cause mortality, random-effects meta-analysis
MeSH terms: Bayes Theorem, Humans, Research Design, Meta-Analysis as Topic, Outcome Assessment, Health Care

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Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

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