Design of platform trials with a change in the control treatment arm
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.
Authors
- Thomas Jaki (ORCID: https://orcid.org/0000-0002-1096-188X)
- Pavel Mozgunov (ORCID: https://orcid.org/0000-0001-6810-0284)
- Peter Greenstreet (ORCID: https://orcid.org/0000-0002-4997-8742)
- Alun Bedding
Institutions
- University of Cambridge (GB)
- Ottawa Hospital (CA)
- MRC Biostatistics Unit (GB)
- University of Regensburg (DE)
- Lancaster University (GB)
Publication Details
- Journal
- Biometrics
- Published
- 2025-04-02
- DOI
- https://doi.org/10.1093/biomtc/ujaf073
- Citations
- 1
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 2.63
Funders
- National Institute for Health and Care Research
- Department of Health and Social Care
- Canadian Institutes of Health Research
- Medical Research Council
- Engineering and Physical Sciences Research Council