Design of platform trials with a change in the control treatment arm

Greenstreet, Peter and Jaki, Thomas and Bedding, Alun and Mozgunov, Pavel (2025) Design of platform trials with a change in the control treatment arm. BIOMETRICS, 81 (2): ujaf073. ISSN 0006-341X, 1541-0420

Full text not available from this repository. (Request a copy)

Abstract

Platform trials are an efficient way of testing multiple treatments. We consider platform trials where, if a treatment is found to be superior to the control, it will become the new standard of care. The remaining treatments are then tested against this new control. In this setting, one can either keep the information on both the new standard of care and the other active treatments before the control is changed or discard this information when testing for benefit of the remaining treatments. We show analytically and numerically, retaining the information collected before the change in control can be detrimental to the power in a frequentist multi-arm multi-stage trial. Specifically, we consider the overall power, the probability that the active treatment with the greatest treatment effect is found during the trial, and the conditional power, the probability a given treatment is found superior against the current control. Also studied is the conditional type I error, the probability a given treatment is incorrectly found superior against the current control. We prove when retaining the information decreases both the overall and conditional power but also decreases the conditional type I error. A motivating example is then studied. Based on these observations, we discuss different aspects to consider when deciding whether to run a continuous platform trial or run an inherently new trial using the same trial infrastructure.

Item Type: Article
Uncontrolled Keywords: SEQUENTIAL DESIGNS; change in control; frequentist trials; multi-arm; multi-stage; platform trials
Subjects: 000 Computer science, information & general works > 004 Computer science
Divisions: Informatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki)
Depositing User: Dr. Gernot Deinzer
Date Deposited: 28 Jul 2026 08:50
Last Modified: 28 Jul 2026 08:50
URI: https://pred.uni-regensburg.de/id/eprint/67293

Actions (login required)

View Item View Item