Evaluating the Quality of Evidence from a Network Meta-Analysis

Evaluating the Quality of Evidence from a Network Meta-Analysis

July 3, 2014 | Georgia Salanti1, Cinzia Del Giovane2, Anna Chaimani1, Deborah M. Caldwell3, Julian P. T. Higgins3,4*
The article "Evaluating the Quality of Evidence from a Network Meta-Analysis" by Salanti et al. proposes a method to assess the confidence in the results of network meta-analyses, which are used to evaluate the relative effectiveness of multiple interventions. The authors draw on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework, adapted to address the specific issues in network meta-analyses. They emphasize the importance of considering indirect comparisons, the contributions of direct evidence, the transitivity assumption, and the potential disagreement between direct and indirect evidence. The proposed framework evaluates the quality of evidence for both pairwise effect sizes and treatment rankings, using five components: study limitations, inconsistency, indirectness, imprecision, and publication bias. The authors apply this framework to a systematic review comparing topical antibiotics without steroids for chronically discharging ears with underlying eardrum perforations, illustrating how to determine the confidence in the results and the impact of different sources of evidence on the overall quality of the network meta-analysis.The article "Evaluating the Quality of Evidence from a Network Meta-Analysis" by Salanti et al. proposes a method to assess the confidence in the results of network meta-analyses, which are used to evaluate the relative effectiveness of multiple interventions. The authors draw on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework, adapted to address the specific issues in network meta-analyses. They emphasize the importance of considering indirect comparisons, the contributions of direct evidence, the transitivity assumption, and the potential disagreement between direct and indirect evidence. The proposed framework evaluates the quality of evidence for both pairwise effect sizes and treatment rankings, using five components: study limitations, inconsistency, indirectness, imprecision, and publication bias. The authors apply this framework to a systematic review comparing topical antibiotics without steroids for chronically discharging ears with underlying eardrum perforations, illustrating how to determine the confidence in the results and the impact of different sources of evidence on the overall quality of the network meta-analysis.
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