Mitigating Disputes Originated by Multiple Discordant Systematic Reviews and Meta-Analyses: A Survey of Methodologists and Clinicians - Puljak, Livia; Parmelli, Elena; Capobussi, Matteo; Gonzalez-Lorenzo, Marien; Squizzato, Alessandro; Moja, Lorenzo; Riva, Nicoletta (Frontiers in Research Metrics and Analytics, 2022)
Background: Overlapping systematic reviews (SRs) are increasingly frequent in the medical literature. They can easily generate discordant evidence, as estimates of effect sizes and their interpretation might differ from one source to another. Objective: To analyze how methodologists and clinicians make a decision when faced with discordant evidence formalized in structured tables. Methods: We conducted a 16-item survey exploring how methodologists and clinicians would react when presented with multiple Summary of Findings (SoF) tables (generated using the GRADE tool) derived from four overlapping and discordant SRs and meta-analyses on thrombolytic therapy for intermediate-risk pulmonary embolism. SoF tables reported four different magnitudes of effects and overall certainty. Participants were asked to provide their recommendations regarding the intervention and the reasons behind their conclusion. Results: Of the 80 invitees, 41 (51%) participated. The majority described themselves as ‘somewhat familiar’ or experts with SoF tables. The majority recommended the therapy (pharmacological systemic thrombolysis), grading the recommendation as weak positive. Certainty of evidence and benefit-risk balance were the two criteria that prevailed in generating the recommendation. When faced with overlapping meta-analyses, the preferred approach was to use only high-quality SRs and exclude redundant SRs. Several participants suggested integrating the SoF tables with additional information, such as a more comprehensive evaluation of the risk of bias of systematic reviews (71%), heterogeneity/inconsistency (68%) and studies included within each SR (62%). Conclusion: When faced with multiple controversial SR results, the type and completeness of reported information in SoF tables affect experts’ ability to make recommendations. Developers of the SoF table should consider collating key information from overlapping and potentially discordant reviews.