Contextual aggregation and rapid updating of trial outcomes within a user-friendly open-source environment

TL;DR

This paper introduces an open-source software tool that aggregates clinical trial data, enabling rapid contextual analysis of new trial outcomes using classical and Bayesian models, thereby improving interpretability and educational utility.

Contribution

The authors developed a user-friendly, open-source platform that combines a large trial database with advanced meta-analytical models for immediate contextual interpretation.

Findings

Demonstrated with a recent epilepsy trial data

Facilitates instant interpretation of new results

Enhances global health research collaboration

Abstract

The delayed and incomplete availability of historical findings and the lack of integrative and user-friendly software hampers the reliable interpretation of new clinical data. We developed a free, open, and user-friendly clinical trial aggregation program combining a large and representative sample of existing trial data with the latest classical and Bayesian meta-analytical models, including clear output visualizations. Our software is of particular interest for (post-graduate) educational programs (e.g., medicine, epidemiology) and global health initiatives. We demonstrate the database, interface, and plot functionality with a recent randomized controlled trial on effective epileptic seizure reduction in children treated for a parasitic brain infection. The single trial data is placed into context and we show how to interpret new results against existing knowledge instantaneously. Our program is of particular interest to those working on the contextualizing of medical findings. It may facilitate the advancement of global clinical progress as efficiently and openly as possible and simulate further bridging clinical data with the latest biostatistical models.