Small study effects in meta-analyses of osteoarthritis trials: meta-epidemiological study
Open accessAbstract
OBJECTIVE: To examine the presence and extent of small study effects in clinical osteoarthritis research. DESIGN: Meta-epidemiological study. DATA SOURCES: 13 meta-analyses including 153 randomised trials (41 605 patients) that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patients' reported pain as an outcome. METHODS: We compared estimated benefits of treatment between large trials (at least 100 patients per arm) and small trials, explored funnel plots supplemented with lines of predicted effects and contours of significance, and used three approaches to estimate treatment effects: meta-analyses including all trials irrespective of sample size, meta-analyses restricted to large trials, and treatment effects predicted for large trials. RESULTS: On average, treatment effects were more beneficial in small than in large trials (difference in effect sizes -0.21, 95% confidence interval -0.34 to -0.08, P=0.001). Depending on criteria used, six to eight funnel plots indicated small study effects. In six of 13 meta-analyses, the overall pooled estimate suggested a clinically relevant, significant benefit of treatment, whereas analyses restricted to large trials and predicted effects in large trials yielded smaller non-significant estimates. CONCLUSIONS: Small study effects can often distort results of meta-analyses. The influence of small trials on estimated treatment effects should be routinely assessed.
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Small studies in osteoarthritis meta-analyses generally showed greater treatment effects than studies with at least 100 participants in each arm.
“Research into the effect of small studies on meta-analyses of osteoarthritis trials found that small studies generally showed greater treatment effects than studies with at least 100 participants in each arm of the trial (Nuesch 2010)”
From Hypnosis for pain management during labour and childbirth (2016) · cites this paper as Nuesch 2010
Small studies of fewer than 100 participants per arm are at increased risk of random effects in estimating both the direction and magnitude of treatment effects.
“small studies of fewer than 100 participants per arm (Moore 2010; Nüesch 2010) are at increased risk of succumbing to the random effects in estimating both direction and magnitude of treatment effects”
From Physical activity and exercise for chronic pain in adults: an overview of Cochrane Reviews (2017) · cites this paper as Nüesch 2010
The persistent evidence of small study effects, as well as the significant heterogeneity, casts doubts over the reliability of the large effects observed for anxiety.
“The persistent evidence of small study effects, as well as the significant heterogeneity, y casts doubts over the reliability of the large effects observed for anxiety25,37,38.”
From The effectiveness of virtual reality based interventions for symptoms of anxiety and depression: A meta-analysis (2018) · cites this paper as [38]
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Green and black tea for the primary prevention of cardiovascular disease
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Viscosupplementation for Osteoarthritis of the Knee
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Dietary fibre for the primary prevention of cardiovascular disease
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- Authors
- Nuesch, E., Trelle, S., Reichenbach, S., Rutjes, A. W. S., Tschannen, B., Altman, D. G., Egger, M., & Juni, P.
- Affiliations
- University of Bern (CH)
- University of Oxford (GB)
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2010-07-16
- Volume
- 341
- Issue
- jul16 1
- Pages
- c3515-c3515
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- PMC
- PMC2905513
- OpenAlex
- W2063738853
- Cited by
- 559
- References
- 62
- Citations by year
- 2026: 13 · 2025: 28 · 2024: 28 · 2023: 15 · 2022: 25 · 2021: 27 · 2020: 22 · 2019: 41 · 2018: 43 · 2017: 63 · 2016: 59 · 2015: 48 · 2014: 47 · 2013: 44 · 2012: 28
- FWCI
- 32.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- BMJ (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- IRIS UNIMORE (University of Modena and Reggio Emilia) (submittedVersion, cc-by-nc)
- BORIS (University Library Bern) (submittedVersion, cc-by-nc)
- Open Access CRIS of the University of Bern
- Funders
- National Science Foundation
- Cancer Research UK
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (115067, 104762, 66377, 066377, 66378)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- small-study effects, osteoarthritis, hip osteoarthritis, knee osteoarthritis, meta-epidemiology, trial size, treatment effect estimation, pain outcomes, funnel plot, publication bias
- MeSH terms
- Humans, Pain, Osteoarthritis, Hip, Randomized Controlled Trials as Topic, Treatment Outcome, Sample Size, Osteoarthritis, Knee
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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