期刊
STATISTICAL METHODS IN MEDICAL RESEARCH
卷 30, 期 3, 页码 717-730出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/0962280220973697
关键词
Adaptive design; Bayesian; clinical trials; decision theory; multi-arm multi-stage trials
类别
资金
- Dutch Cancer Society [KWF 2012-5711]
This paper proposes a generic Bayesian adaptive decision-theoretic design for multi-arm multi-stage clinical trials, which makes decisions about trial continuation based on expected loss reduction. The study shows that this design increases the probability of making a correct decision at the end of the trial compared to nonadaptive and adaptive two-stage designs through simulation.
Multi-arm multi-stage clinical trials in which more than two drugs are simultaneously investigated provide gains over separate single- or two-arm trials. In this paper we propose a generic Bayesian adaptive decision-theoretic design for multi-arm multi-stage clinical trials with K (K >= 2) arms. The basic idea is that after each stage a decision about continuation of the trial and accrual of patients for an additional stage is made on the basis of the expected reduction in loss. For this purpose, we define a loss function that incorporates the patient accrual costs as well as costs associated with an incorrect decision at the end of the trial. An attractive feature of our loss function is that its estimation is computationally undemanding, also when K > 2. We evaluate the frequentist operating characteristics for settings with a binary outcome and multiple experimental arms. We consider both the situation with and without a control arm. In a simulation study, we show that our design increases the probability of making a correct decision at the end of the trial as compared to nonadaptive designs and adaptive two-stage designs.
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