Effects of study precision and risk of bias in networks of interventions: a network meta-epidemiological study

Chaimani, Anna; Vasiliadis, Haris S.; Pandis, Nikolaos; Schmid, Christopher H.; Welton, Nicky J.; Salanti, Georgia (2013). Effects of study precision and risk of bias in networks of interventions: a network meta-epidemiological study. International journal of epidemiology, 42(4), pp. 1120-1031. Oxford University Press 10.1093/ije/dyt074

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BACKGROUND Empirical research has illustrated an association between study size and relative treatment effects, but conclusions have been inconsistent about the association of study size with the risk of bias items. Small studies give generally imprecisely estimated treatment effects, and study variance can serve as a surrogate for study size. METHODS We conducted a network meta-epidemiological study analyzing 32 networks including 613 randomized controlled trials, and used Bayesian network meta-analysis and meta-regression models to evaluate the impact of trial characteristics and study variance on the results of network meta-analysis. We examined changes in relative effects and between-studies variation in network meta-regression models as a function of the variance of the observed effect size and indicators for the adequacy of each risk of bias item. Adjustment was performed both within and across networks, allowing for between-networks variability. RESULTS Imprecise studies with large variances tended to exaggerate the effects of the active or new intervention in the majority of networks, with a ratio of odds ratios of 1.83 (95% CI: 1.09,3.32). Inappropriate or unclear conduct of random sequence generation and allocation concealment, as well as lack of blinding of patients and outcome assessors, did not materially impact on the summary results. Imprecise studies also appeared to be more prone to inadequate conduct. CONCLUSIONS Compared to more precise studies, studies with large variance may give substantially different answers that alter the results of network meta-analyses for dichotomous outcomes.

Item Type:

Journal Article (Original Article)


04 Faculty of Medicine > Other Institutions > Teaching Staff, Faculty of Medicine
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine
04 Faculty of Medicine > School of Dental Medicine > Department of Orthodontics

UniBE Contributor:

Pandis, Nikolaos


600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services




Oxford University Press




Eveline Carmen Schuler

Date Deposited:

04 Apr 2014 10:25

Last Modified:

27 Apr 2018 10:11

Publisher DOI:


PubMed ID:


Uncontrolled Keywords:

Multiple-treatments meta-analysis; indirect comparison; mixed-treatment comparison; publication bias; small-study effects





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