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RaBIt:An Effective Visualization-Driven Tool for Power and Sample Size Estimation in Two-Stage General Randomized Basket Trial Designs

Chen, D. Z.; Patel, S. S.; Xie, A.; Chen, J.; Castle, D.; Ma, C.

2024-09-22 oncology
10.1101/2024.09.19.24313989 medRxiv
Show abstract

Basket trial designs with interim analysis have gained significant attention due to their adaptability, flexibility, and scalability. In response to the need for user-friendly tools that enhance the real-world applicability of these designs, we developed a web-based interface aimed at facilitating two-stage basket trial designs. Built using R Shiny, the tool was rigorously validated for output consistency by comparing it to an established R pipeline. Additionally, user testing was conducted to ensure the interface is intuitive and easy to use. The result is a freely accessible tool that provides effective and convenient visualizations for general basket trial designs with interim analysis, available at https://desmondzeyachen.shinyapps.io/AdaptiveTwoStageBasketTrialFeb14/. Future improvements may further expand the tools capabilities to accommodate the increasing complexity of trial designs needed by the research community.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.