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Investigating clinical heterogeneity in systematic reviews: a methodologic review of guidance in the literature
Open accessAbstract
BACKGROUND: While there is some consensus on methods for investigating statistical and methodological heterogeneity, little attention has been paid to clinical aspects of heterogeneity. The objective of this study is to summarize and collate suggested methods for investigating clinical heterogeneity in systematic reviews. METHODS: We searched databases (Medline, EMBASE, CINAHL, Cochrane Library, and CONSORT, to December 2010) and reference lists and contacted experts to identify resources providing suggestions for investigating clinical heterogeneity between controlled clinical trials included in systematic reviews. We extracted recommendations, assessed resources for risk of bias, and collated the recommendations. RESULTS: One hundred and one resources were collected, including narrative reviews, methodological reviews, statistical methods papers, and textbooks. These resources generally had a low risk of bias, but there was minimal consensus among them. Resources suggested that planned investigations of clinical heterogeneity should be made explicit in the protocol of the review; clinical experts should be included on the review team; a set of clinical covariates should be chosen considering variables from the participant level, intervention level, outcome level, research setting, or others unique to the research question; covariates should have a clear scientific rationale; there should be a sufficient number of trials per covariate; and results of any such investigations should be interpreted with caution. CONCLUSIONS: Though the consensus was minimal, there were many recommendations in the literature for investigating clinical heterogeneity in systematic reviews. Formal recommendations for investigating clinical heterogeneity in systematic reviews of controlled trials are required.
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“A minimum of 10 studies included in each meta-analysis was considered sufficient for heterogeneity values to be deemed reliable [45].”
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Metadata
- Authors
- Gagnier, J. J., Moher, D., Boon, H., Beyene, J., & Bombardier, C.
- Affiliations
- University of Michigan (US)
- University of Ottawa (CA)
- University of Toronto (CA)
- Hospital for Sick Children (CA)
- Corresponding author
- Gagnier, Joel J
- Venue
- BMC Medical Research Methodology
- Published
- 2012-07-30
- Volume
- 12
- Issue
- 1
- Pages
- 111-111
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC3564789
- OpenAlex
- W1990368073
- Cited by
- 222
- References
- 127
- Citations by year
- 2026: 17 · 2025: 24 · 2024: 24 · 2023: 21 · 2022: 24 · 2021: 37 · 2020: 19 · 2019: 22 · 2018: 5 · 2017: 7 · 2016: 5 · 2015: 9 · 2014: 5 · 2013: 3
- FWCI
- 1.50
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Research Methodology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- TSpace (University of Toronto) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- uO Research (University of Ottawa) (submittedVersion, public-domain)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Sociology and Political Science › Delphi Technique in Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Keywords
- clinical heterogeneity, covariate selection, risk of bias, methodological recommendations, subgroup analysis
- MeSH terms
- Systematic Reviews as Topic, Bayes Theorem, Clinical Trials as Topic, Data Interpretation, Statistical, Humans, Meta-Analysis as Topic, Epidemiologic Research Design, Bias, Databases, Bibliographic, Controlled Clinical Trials as Topic, Evidence-Based Medicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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