Open AccessUnified exact design with early stopping rules for single arm clinical trials with multiple endpoints
Author(s) -
Wei Wei,
Denise Esserman,
Michael J. Kane,
Daniel Zelterman
Publication year - 2021
Publication title -
statistical methods in medical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.952
H-Index - 85
eISSN - 1477-0334
pISSN - 0962-2802
DOI - 10.1177/09622802211013062
Subject(s) - computer science , interim , early stopping , interim analysis , construct (python library) , adaptive design , clinical study design , clinical trial , popularity , machine learning , medicine , programming language , psychology , social psychology , artificial neural network , history , archaeology , pathology
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.