Journal impact factor, trial effect size, and methodological quality appear scantly related: a systematic review and meta-analysis.

BACKGROUND: As systematic reviews' limited coverage of the medical literature necessitates decision-making based on unsystematic review, we investigated a possible advantage of systematic review (aside from dataset size and systematic analysis): does systematic review avoid potential bias in sampling primary studies from high impact factor journals? If randomized controlled trials (RCTs) reported in higher-impact journals present different treatment benefits than RCTs reported in lower-impact journals, readers who focus on higher-impact journals for their rapid literature reviews may introduce bias which could be mitigated by complete, systematic sampling. METHODS: We randomly sampled Cochrane Library (20 July 2005) treatment reviews that measured mortality as a binary outcome, published in English or French, with at least five RCTs with one or more deaths. Our domain-based assessment of risk of bias included funding source, randomness of allocation sequence, blinding, and allocation concealment. The primary analysis employed logistic regression by a generalized linear model with a generalized estimating equation to estimate the association between various factors and publication in a journal with a high journal impact factor (JIF). RESULTS: From the 29 included systematic reviews, 189 RCTs contributed data. However, in the primary analyses comparing RCT results within meta-analyses, there was no statistically significant association: unadjusted odds of greater than 50% mortality protection in high-JIF (> 5) journals were 1.4 (95% CI 0.42, 4.4) and adjusted, 2.5 (95% CI 0.6, 10). Elements of study quality were weakly, inconsistently, and not statistically significantly correlated with journal impact factor. CONCLUSIONS: Journal impact factor may have little to no association with study results, or methodological quality, but the evidence is very uncertain.