Affiliation:
1. Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
Abstract
Adaptive designs are gaining popularity in early phase clinical trials because they enable investigators to change the course of a study in response to accumulating data. We propose a novel design to simultaneously monitor several endpoints. These include efficacy, futility, toxicity and other outcomes in early phase, single-arm studies. We construct a recursive relationship to compute the exact probabilities of stopping for any combination of endpoints without the need for simulation, given pre-specified decision rules. The proposed design is flexible in the number and timing of interim analyses. A R Shiny app with user-friendly web interface has been created to facilitate the implementation of the proposed design.
Funder
Center for Information Technology
Pilot Grant from Yale Cancer Center
Subject
Health Information Management,Statistics and Probability,Epidemiology
Cited by
1 articles.
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