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Cited by 295Meta-analysis and systematic reviewsStatistical Methods in Clinical TrialsStatistical Methods in Epidemiology

The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.

Small studies may overestimate the effect sizes in critical care meta-analyses: a meta-epidemiological study

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Zhang, Zhongheng, Xu, Xiao, Ni, Hongying·2013·Critical Care
DOI 10.1186/cc11919PMC PMC4056100
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Abstract

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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  1. Zarychanski R, Turgeon AF, Fergusson DA, Cook DJ, Hébert P, Bagshaw SM, Monsour D, McIntyre L: Renal outcomes and mortality following hydroxyethyl starch resuscitation of critically ill patients: systematic review and meta-analysis of randomized trials. Open Med 2009, 3: e196-209.

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Metadata

Authors
Zhang, Z., Xu, X., & Ni, H.
Affiliations
Jinhua Central Hospital (CN)
Corresponding author
Zhang, Zhongheng
ORCID
Venue
Critical Care
Publisher
Springer Science and Business Media LLC
Published
2013-01-09
Volume
17
Issue
1
Pages
R2-R2
ISSN
1364-8535 (ISSN-L)
DOI
10.1186/cc11919
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
Licence
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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