Reporting and evaluation of assumptions and certainty of evidence in network meta-analyses

Abstract Network meta-analysis (NMA) facilitates the comparison of multiple treatments by integrating both direct and indirect evidence. Applications of NMA in medical decision making have grown exponentially. However, the validity of NMA findings depends on key assumptions: homogeneity, transitivity, and consistency. A lack of consistent assessment of these assumptions potentially compromises the reliability of NMA outcomes. The objective of this study is to evaluate the extent to which researchers address NMA assumptions and report the assessment of evidence certainty in NMA publications. A total of 22,079 studies were identified from PubMed, Embase, and Cochrane CENTRAL (January 2010–August 2024). A sample of 393 NMAs was calculated to represent this population and randomly selected. Data on study characteristics, NMA assumptions, and the certainty of evidence were extracted and analyzed descriptively. Of the 393 NMAs, 71.8% were published between 2020 and 2024. Homogeneity was assessed in 300 (76.3%) NMAs, transitivity in 45 (11.5%) NMAs, and consistency in 265 (67.4%) NMAs. The certainty of evidence was assessed in 110 (28.0%) studies, predominantly using GRADE (71 NMAs; 18.1%) or CINeMA (29 NMAs; 7.4%). NMAs published in journals with high-impact factors more frequently evaluate these aspects than those published in low-impact journals. The assessment of NMA assumptions is inconsistently reported across studies, particularly for transitivity and consistency assumptions. Our findings highlight the need for standardized protocols or reporting guidelines to ensure these assessments are conducted and transparently reported.