Methods/Statistics
An accessible web-based solution for network meta-analysis integrating frequentist and Bayesian methods Janos Tibor Fekete* Janos Tibor Fekete Fekete Semmelweis University, Dept. of Bioinformatics, Budapest, Hungary
Background: Network meta-analysis (NMA) is a methodological framework for comparing multiple interventions in the absence of head-to-head trials. However, conducting NMA often requires advanced statistical expertise and specialized software. The objective of this study was to establish a framework for transparent and reproducible network meta-analysis.
Methods: We established NetMetaEasy, a web-based platform for conducting network meta-analysis of user-provided data using both frequentist and Bayesian methods, enabling both frequentist and Bayesian analytical options within the same analytical environment. As a demonstration use case, aggregated data from phase III trials of cyclin-dependent kinase 4/6 (CDK4/6) inhibitors in hormone receptor–positive early breast cancer were analyzed using a frequentist hazard ratio–based network meta-analysis with disease–free survival (DFS) as the endpoint.
Results: In the CDK4/6 inhibitor demonstration, ribociclib plus endocrine therapy (ET) showed the strongest improvement in DFS compared with ET alone (HR 0.72; 95% CI 0.62–0.83). Our results illustrate that direct and indirect evidence can be rapidly synthesized and compared within a network meta-analysis framework implemented through a web-based analytical environment.
Conclusions: NetMetaEasy provides an accessible, web-based solution for conducting network meta-analysis, integrating frequentist and Bayesian methods within a single inte A Unified Web-Based Environment for Conducting Network Meta-Analysisrface. By lowering technical barriers and supporting transparent, reproducible workflows, the platform facilitates methodological teaching and applied comparative effectiveness research. The new platform is accessible at https://metaanalysisonline.com/netmetaeasy.