Multi-arm multi-stage (MAMS) trials can improve the efficiency of the drug development process when multiple new treatments are available for testing. A group-sequential approach can be used in order to design MAMS trials, using an extension to the Dunnett multiple testing procedure. The actual sample size used in such a trial is a random variable which has high variability. This can cause problems when applying for funding as the cost will generally also be highly variable. This motivates a type of design which provides the efficiency advantages of a group-sequential MAMS design, but has a fixed sample size. One such design is the two-stage drop-the-losers design, in which a number of experimental treatments, and a control treatment, are assessed at a pre-scheduled interim analysis. The best performing experimental treatment and the control treatment then continue to a second stage. In this paper we discuss extending this design to have more than two stages, which is shown to considerably reduce the sample size required. We also compare the resulting sample size requirements to the sample size distribution of analogous group-sequential MAMS designs. The sample size required for a multistage drop-the-losers design is usually higher than, but close to, the median sample size of a group-sequential MAMS trial. In many practical scenarios, the disadvantage of a slight loss in average efficiency would be overcome by the huge advantage of a fixed sample size. We assess the impact of delay between recruitment and assessment as well as unknown variance on the drop-the-losers designs.
- clinical trial design
- group-sequential designs
- interim analysis
- multi-arm multi-stage designs
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- Department of Mathematical Sciences - Professor
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
Person: Research & Teaching