Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013;8(3):e59202.
doi: 10.1371/journal.pone.0059202. Epub 2013 Mar 27.

The impact of study size on meta-analyses: examination of underpowered studies in Cochrane reviews

Rebecca M Turner  1 , Sheila M Bird, Julian P T Higgins
Affiliations

The impact of study size on meta-analyses: examination of underpowered studies in Cochrane reviews

Rebecca M Turner et al. PLoS One. 2013.

Abstract

Background: Most meta-analyses include data from one or more small studies that, individually, do not have power to detect an intervention effect. The relative influence of adequately powered and underpowered studies in published meta-analyses has not previously been explored. We examine the distribution of power available in studies within meta-analyses published in Cochrane reviews, and investigate the impact of underpowered studies on meta-analysis results.

Methods and findings: For 14,886 meta-analyses of binary outcomes from 1,991 Cochrane reviews, we calculated power per study within each meta-analysis. We defined adequate power as ≥50% power to detect a 30% relative risk reduction. In a subset of 1,107 meta-analyses including 5 or more studies with at least two adequately powered and at least one underpowered, results were compared with and without underpowered studies. In 10,492 (70%) of 14,886 meta-analyses, all included studies were underpowered; only 2,588 (17%) included at least two adequately powered studies. 34% of the meta-analyses themselves were adequately powered. The median of summary relative risks was 0.75 across all meta-analyses (inter-quartile range 0.55 to 0.89). In the subset examined, odds ratios in underpowered studies were 15% lower (95% CI 11% to 18%, P<0.0001) than in adequately powered studies, in meta-analyses of controlled pharmacological trials; and 12% lower (95% CI 7% to 17%, P<0.0001) in meta-analyses of controlled non-pharmacological trials. The standard error of the intervention effect increased by a median of 11% (inter-quartile range -1% to 35%) when underpowered studies were omitted; and between-study heterogeneity tended to decrease.

Conclusions: When at least two adequately powered studies are available in meta-analyses reported by Cochrane reviews, underpowered studies often contribute little information, and could be left out if a rapid review of the evidence is required. However, underpowered studies made up the entirety of the evidence in most Cochrane reviews.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: RMT and JPTH declare that no competing interests exist. The authors have the following interest. SMB holds Glaxo shares. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

Figures

Figure 1
Figure 1. Distribution of power available to detect a relative risk reduction of 30%, across 77,237 studies.
See this image and copyright information in PMC

References

    1. Sterne JAC, Gavaghan D, Egger M (2000) Publication and related bias in meta-analysis: power of statistical tests and prevalence in the literature. Journal of Clinical Epidemiology 53: 1119–29. - PubMed
    1. Nygard O, Vollset SE, Refsum H, Stensvold I, Tverdal A, et al. (1995) Total plasma homocysteine and cardiovascular risk profile. JAMA 274: 1526–33. - PubMed
    1. Kjaergard LL, Villumsen J, Gluud C (2001) Reported methodologic quality and discrepancies between large and small randomized trials in meta-analyses. Annals of Internal Medicine 135: 982–9. - PubMed
    1. Stanley TD, Jarrell SB, Doucouliagos H (2010) Could it be better to discard 90% of the data? A statistical paradox. The American Statistician 64: 70–7.
    1. Kraemer HC, Gardner C, Brooks III JO, Yesavage JA (1998) Advantages of excluding underpowered studies in meta-analysis: inclusionist versus exclusionist viewpoints. Psychological Methods 3: 23–31.

Publication types

LinkOut - more resources