4.4 Article

A multi-arm multi-stage clinical trial design for binary outcomes with application to tuberculosis

期刊

BMC MEDICAL RESEARCH METHODOLOGY
卷 13, 期 -, 页码 -

出版社

BIOMED CENTRAL LTD
DOI: 10.1186/1471-2288-13-139

关键词

Multi-arm; Multi-stage; Tuberculosis; Binary outcome; Adaptive design; Treatment selection

资金

  1. MRC [MC_EX_G0800814] Funding Source: UKRI
  2. Medical Research Council [MC_EX_G0800814] Funding Source: Medline
  3. Medical Research Council [MC_EX_G0800814] Funding Source: researchfish

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Background: Randomised controlled trials are becoming increasingly costly and time-consuming. In 2011, Royston and colleagues proposed a particular class of multi-arm multi-stage (MAMS) designs intended to speed up the evaluation of new treatments in phase II and III clinical trials. Their design, which controls the type I error rate and power for each pairwise comparison, discontinues randomisation to poorly performing arms at interim analyses if they fail to show a pre-specified level of benefit over the control arm. Arms in which randomisation is continued to the final stage of the trial are compared against the control on a definitive time-to-event outcome measure. To increase efficiency, interim comparisons can be made on an intermediate time-to-event outcome which is on the causal pathway to the definitive outcome. Methods: We adapt Royston's MAMS design to binary outcomes observed at the end of a fixed follow-up period and analysed using an absolute difference in proportions. We apply the design to tuberculosis (TB), an area where many new drugs are in development, and demonstrate how it can greatly accelerate the evaluation of new TB regimens. We use simulations to support the extensions to the methodology and to investigate the amount of bias in the estimated treatment effects of arms in which randomisation is ceased at the first interim analysis and arms which continue to the final stage of the trial. Results: The proposed seamless phase II/III TB trial designs are shown to greatly reduce sample size requirements and trial duration compared to conducting separate phase II and III trials. The bias in the estimated treatment effects for the definitive outcome is shown to be small, especially when treatment selection is based on an intermediate outcome or when a reanalysis is performed at the planned end of the trial after all recruited patients have completed follow-up. Conclusions: The proposed designs are practical and could be used in a variety of disease areas. They hold considerable promise for speeding up the evaluation of new treatments particularly in TB where many new regimens will soon be available for testing in phase II and phase III trials.

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