Accumulating Research: A Systematic Account of How Cumulative Meta-Analyses Would Have Provided Knowledge, Improved Health, Reduced Harm and Saved Resources
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BACKGROUND: "Cumulative meta-analysis" describes a statistical procedure to calculate, retrospectively, summary estimates from the results of similar trials every time the results of a further trial in the series had become available. In the early 1990 s, comparisons of cumulative meta-analyses of treatments for myocardial infarction with advice promulgated through medical textbooks showed that research had continued long after robust estimates of treatment effects had accumulated, and that medical textbooks had overlooked strong, existing evidence from trials. Cumulative meta-analyses have subsequently been used to assess what could have been known had new studies been informed by systematic reviews of relevant existing evidence and how waste might have been reduced. METHODS AND FINDINGS: We used a systematic approach to identify and summarise the findings of cumulative meta-analyses of studies of the effects of clinical interventions, published from 1992 to 2012. Searches were done of PubMed, MEDLINE, EMBASE, the Cochrane Methodology Register and Science Citation Index. A total of 50 eligible reports were identified, including more than 1,500 cumulative meta-analyses. A variety of themes are illustrated with specific examples. The studies showed that initially positive results became null or negative in meta-analyses as more trials were done; that early null or negative results were over-turned; that stable results (beneficial, harmful and neutral) would have been seen had a meta-analysis been done before the new trial; and that additional trials had been much too small to resolve the remaining uncertainties. CONCLUSIONS: This large, unique collection of cumulative meta-analyses highlights how a review of the existing evidence might have helped researchers, practitioners, patients and funders make more informed decisions and choices about new trials over decades of research. This would have led to earlier uptake of effective interventions in practice, less exposure of trial participants to less effective treatments, and reduced waste resulting from unjustified research.
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Evidence from systematic review can help researchers optimise usefulness of new trial by informing design aspects such as outcome definition and sample size.
“This evidence can also help researchers to optimise the usefulness of the new trial by informing design aspects such as outcome definition and sample size.143 144 145”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [144]
Failure to review the cumulative evidence can lead to trial participants being deprived of effective interventions or exposed to harmful interventions.
“or to trial participants being deprived of effective interventions or exposed to harmful interventions.144 149 150 151”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [144]
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Core outcome sets and trial registries
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“Trial registration contributes to reducing waste in research by helping to avoid unnecessary duplication of effort [2] and making it easier for health and social care research to be cumulative [3].”
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Fostering responsible research practices is a shared responsibility of multiple stakeholders
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Scoping Reviews and Their Role in Reducing Research Waste
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Self-citationRedundant trials can be prevented, if the EU clinical trial regulation is applied duly
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Dexamethasone in Patients with Spontaneous Intracerebral Hemorrhage: An Updated Meta-Analysis
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Trends of Randomized Clinical Trials Citing Prior Systematic Reviews, 2007-2021
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Systematic review and meta-analysis: tools for the information age
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Systematic reviews and meta-analysis in rheumatology: a gentle introduction for clinicians
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Sharing Knowledge for Health Care
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Extrapolation will never replace randomized clinical trials
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Interpreting and Implementing Evidence for Quality Research
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- Authors
- Clarke, M., Brice, A., & Chalmers, I.
- Affiliations
- Queen's University Belfast (GB)
- Corresponding author
- Clarke, Mike
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-07-28
- Volume
- 9
- Issue
- 7
- Pages
- e102670
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4113310
- OpenAlex
- W2087358018
- Cited by
- 120
- References
- 74
- Citations by year
- 2026: 5 · 2025: 12 · 2024: 11 · 2023: 15 · 2022: 9 · 2021: 11 · 2020: 9 · 2019: 7 · 2018: 6 · 2017: 10 · 2016: 13 · 2015: 9 · 2014: 3
- FWCI
- 11.42
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (Queen's University Belfast) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmaceutical industry and healthcare
- Keywords
- cumulative meta-analysis, research waste, clinical trial design, treatment effect heterogeneity, negative results, research funding allocation, evidence-based decision making, myocardial infarction treatment, medical textbooks
- MeSH terms
- Health Status, Humans, Harm Reduction, Resource Allocation
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.
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