NetMetaEasy: enabling rapid and user-friendly network meta-analysis (NMA) for comparative effectiveness research

Area of Science:

• Pharmacology and Biostatistics
• Evidence Synthesis and Meta-Analysis

Background:

• Network meta-analysis (NMA) is crucial for comparing multiple treatments but requires specialized statistical expertise and software.
• Wider adoption of NMA is hindered by its complexity and accessibility barriers for many researchers.

Purpose of the Study:

• To introduce NetMetaEasy, a web-based platform designed for user-friendly execution and visualization of network meta-analyses.
• To lower the technical barrier for performing NMA, enabling broader application in research and clinical guidelines.

Main Methods:

• NetMetaEasy is an R/Shiny platform supporting binary, continuous, and summary-effect data.
• It offers both frequentist and Bayesian NMA with P-score and SUCRA ranking.
• Utilizes netmeta and gemtc R packages for fixed- and random-effects models, generating standard NMA outputs.

Main Results:

• The platform successfully performed NMA on a dataset of SGLT2 inhibitors for cardiovascular outcomes.
• NetMetaEasy generated all standard NMA outputs, identified beneficial treatments, and showed no small-study bias.
• The entire analysis workflow, from data upload to interpretation-ready plots, was completed in minutes.

Conclusions:

• NetMetaEasy offers an accessible solution for network meta-analysis, streamlining data processing, analysis, and visualization.
• The platform facilitates more widespread and rapid evidence synthesis in pharmacology, especially for those without advanced statistical training.