Flaws in the application and interpretation of statistical analyses in systematic reviews of therapeutic interventions were common: a cross-sectional analysis

Abstract

Objectives: The objective of the study was to investigate the application and interpretation of statistical analyses in a cross-section of systematic reviews (SRs) of therapeutic interventions, without restriction by journal, clinical condition, or specialty.

Study design and setting: We evaluated a random sample of SRs assembled previously, which were indexed in MEDLINE® during February 2014, focused on a treatment or prevention question, and reported at least one meta-analysis. The reported statistical methods used in each SR were extracted from articles and online appendices by one author, with a 20% random sample extracted in duplicate.

Results: We evaluated 110 SRs; 78/110 (71%) were non-Cochrane SRs and 55/110 (50%) investigated a pharmacological intervention. The SRs presented a median of 13 (interquartile range: 5-27) meta-analytic effects. When considering the index (primary or first reported) meta-analysis of each SR, just over half (62/110 [56%]) used the random-effects model, but few (5/62 [8%]) interpreted the meta-analytic effect correctly (as the average of the intervention effects across all studies). A statistical test for funnel plot asymmetry was reported in 17/110 (15%) SRs; however, in only 4/17 (24%) did the test include the recommended number of at least 10 studies of varying size. Subgroup analyses accompanied 42/110 (38%) index meta-analyses, but findings were not interpreted with respect to a test for interaction in 29/42 (69%) cases, and the issue of potential confounding in the subgroup analyses was not raised in any SR.

Conclusions: There is scope for improvement in the application and interpretation of statistical analyses in SRs of therapeutic interventions. The involvement of statisticians on the SR team and establishment of partnerships between researchers with specialist expertise in SR methods and journal editors may help overcome these shortcomings.

Keywords: Meta-analysis; Meta-research; Methodology; Quality; Reporting; Systematic reviews.