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

arXiv (Cornell University)(2023)

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摘要
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.
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关键词
trial outcomes,contextual aggregation,user-friendly,open-source
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