Abstract
For the cancer clinical trials with immunotherapy and molecularly targeted therapy, time-to-event endpoint is often a desired endpoint. In this paper, we present an event-driven approach for Bayesian one-stage and two-stage single-arm phase II trial designs. Two versions of Bayesian one-stage designs were proposed with executable algorithms and meanwhile, we also develop theoretical relationships between the frequentist and Bayesian designs. These findings help investigators who want to design a trial using Bayesian approach have an explicit understanding of how the frequentist properties can be achieved. Moreover, the proposed Bayesian designs using the exact posterior distributions accommodate the single-arm phase II trials with small sample sizes. We also proposed an optimal two-stage approach, which can be regarded as an extension of Simon's two-stage design with the time-to-event endpoint. Comprehensive simulations were conducted to explore the frequentist properties of the proposed Bayesian designs and an R package BayesDesign can be assessed via R CRAN for convenient use of the proposed methods.
Original language | English |
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Pages (from-to) | 1235-1248 |
Number of pages | 14 |
Journal | Pharmaceutical Statistics |
Volume | 20 |
Issue number | 6 |
DOIs | |
State | Published - Nov 1 2021 |
Bibliographical note
Publisher Copyright:© 2021 John Wiley & Sons Ltd.
Keywords
- Bayesian design
- phase II trial
- proportional hazards
- sample size calculation
- time-to-event endpoint
ASJC Scopus subject areas
- Statistics and Probability
- Pharmacology
- Pharmacology (medical)