Small studies may overestimate the effect sizes in critical care meta-analyses: a meta-epidemiological study
Open accessAbstract
INTRODUCTION: Small-study effects refer to the fact that trials with limited sample sizes are more likely to report larger beneficial effects than large trials. However, this has never been investigated in critical care medicine. Thus, the present study aimed to examine the presence and extent of small-study effects in critical care medicine. METHODS: Critical care meta-analyses involving randomized controlled trials and reported mortality as an outcome measure were considered eligible for the study. Component trials were classified as large (≥100 patients per arm) and small (<100 patients per arm) according to their sample sizes. Ratio of odds ratio (ROR) was calculated for each meta-analysis and then RORs were combined using a meta-analytic approach. ROR<1 indicated larger beneficial effect in small trials. Small and large trials were compared in methodological qualities including sequence generating, blinding, allocation concealment, intention to treat and sample size calculation. RESULTS: A total of 27 critical care meta-analyses involving 317 trials were included. Of them, five meta-analyses showed statistically significant RORs <1, and other meta-analyses did not reach a statistical significance. Overall, the pooled ROR was 0.60 (95% CI: 0.53 to 0.68); the heterogeneity was moderate with an I2 of 50.3% (chi-squared = 52.30; P = 0.002). Large trials showed significantly better reporting quality than small trials in terms of sequence generating, allocation concealment, blinding, intention to treat, sample size calculation and incomplete follow-up data. CONCLUSIONS: Small trials are more likely to report larger beneficial effects than large trials in critical care medicine, which could be partly explained by the lower methodological quality in small trials. Caution should be practiced in the interpretation of meta-analyses involving small trials.
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Smaller studies can sometimes overestimate effect sizes even when no true effect is present.
“It is possible that these findings were driven by the fact that smaller studies can sometimes overestimate effect sizes even when no true effect is present (Walum et al., 2016;Zhang et al., 2013).”
From Meta-analytic review of the effects of a single dose of intranasal oxytocin on threat processing in humans (2018) · cites this paper as Zhang et al., 2013
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- Authors
- Zhang, Z., Xu, X., & Ni, H.
- Affiliations
- Jinhua Central Hospital (CN)
- Corresponding author
- Zhang, Zhongheng
- Venue
- Critical Care
- Published
- 2013-01-09
- Volume
- 17
- Issue
- 1
- Pages
- R2-R2
- ISSN
- 1364-8535 (ISSN-L)
- PMC
- PMC4056100
- OpenAlex
- W2066676890
- Cited by
- 295
- References
- 41
- Citations by year
- 2026: 16 · 2025: 18 · 2024: 24 · 2023: 26 · 2022: 30 · 2021: 27 · 2020: 27 · 2019: 27 · 2018: 22 · 2017: 20 · 2016: 19 · 2015: 14 · 2014: 17 · 2013: 8
- FWCI
- 21.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Critical Care (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- 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, sample size, effect size overestimation, mortality, methodological quality of trials, allocation concealment, blinding, incomplete follow-up, meta-epidemiology
- MeSH terms
- Critical Care, Humans, Epidemiologic Studies, Randomized Controlled Trials as Topic
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