Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews
Open accessAbstract
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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This high heterogeneity might be expected for interventions reliant on uptake and adherence to behaviours, and for studies employing various strategies with different durations and intensities.
“This high heterogeneity might be expected for interventions reliant on uptake and adherence to behaviours, and for studies employing various strategies with different durations and intensities.53”
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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
- 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
- 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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