1. Assurance methods for designing a clinical trial with a delayed treatment effect.
- Author
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Salsbury JA, Oakley JE, Julious SA, and Hampson LV
- Subjects
- Humans, Sample Size, Models, Statistical, Neoplasms drug therapy, Neoplasms therapy, Clinical Trials, Phase III as Topic methods, Clinical Trials, Phase III as Topic statistics & numerical data, Clinical Trials as Topic methods, Computer Simulation, Antineoplastic Agents therapeutic use, Time Factors, Survival Analysis, Treatment Delay, Bayes Theorem, Research Design
- Abstract
An assurance calculation is a Bayesian alternative to a power calculation. One may be performed to aid the planning of a clinical trial, specifically setting the sample size or to support decisions about whether or not to perform a study. Immuno-oncology is a rapidly evolving area in the development of anticancer drugs. A common phenomenon that arises in trials of such drugs is one of delayed treatment effects, that is, there is a delay in the separation of the survival curves. To calculate assurance for a trial in which a delayed treatment effect is likely to be present, uncertainty about key parameters needs to be considered. If uncertainty is not considered, the number of patients recruited may not be enough to ensure we have adequate statistical power to detect a clinically relevant treatment effect and the risk of an unsuccessful trial is increased. We present a new elicitation technique for when a delayed treatment effect is likely and show how to compute assurance using these elicited prior distributions. We provide an example to illustrate how this can be used in practice and develop open-source software to implement our methods. Our methodology has the potential to improve the success rate and efficiency of Phase III trials in immuno-oncology and for other treatments where a delayed treatment effect is expected to occur., (© 2024 The Author(s). Statistics in Medicine published by John Wiley & Sons Ltd.)
- Published
- 2024
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