Evaluation of Bayesian adaptive designs for Phase 3 effectiveness trials

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Clinical trials are time consuming, difficult and expensive, and represent a substantial barrier to improving treatments for patients. Researchers and funders have recognised the need for trials to become more efficient, yet the overwhelming majority of trials continue to use traditional methods. A different approach to trials, Bayesian adaptive trial methodology, has been developed over the last 20 years, and has the potential to allow trials to answer their questions more efficiently, often meaning that effectiveness can be determined with fewer patients and in a shorter time. This approach uses Bayesian statistical methods, and includes frequent interim analyses, to allow learning from the trial data collected so far, and subsequent modification of the trial. For example, the proportion of participants allocated to each intervention could be changed to ensure that participants are allocated most efficiently, randomisation to one arm could be stopped, if it has become clear that it is not effective, or the whole trial could be terminated early if it has achieved its aim. These adaptations may enable trials to be run more efficiently, and allow evaluation of more treatments with the same resources.Our aim in this project is to evaluate Bayesian adaptive trial methods, to find out whether they are likely to lead to practical benefits for triallists and funders, in terms of their size, duration and cost. If so, there would be a strong case for using this methodology more widely, and it could potentially become the standard methodology in the future.To evaluate these methods we will perform three studies using data from trials run by the Warwick Clinical Trials Unit. In Study 1, each trial will be redesigned using Bayesian adaptive methods, which will involve producing a number of candidate designs, then performing extensive simulations to understand their performance and to fine-tune their operational parameters such as number and timing of analyses, and threshold values for decisions. A single preferred design will be selected by a group of clinicians and researchers who were not involved in the original trial. The trial will then be re-run, using the original sequence of patients, and we will compare the re-run trial with the original overall duration, number of patients, results, number of patients receiving the more favourable treatment, and cost of the trial. Study 1 will involve four case studies, using trials that had different issues: one that was stopped early because the intervention appeared harmful, one multi-armed trial, one that concluded superiority of its intervention, and one that recruited for a long time but showed no difference.Study 2 will use the same methods as Study 1, but will involve trials that have completed recruitment but have not yet been reported; their results will therefore not yet be known.Study 3 will involve re-designing trials that use a conventional design and are starting or in the early stages of recruitment. In parallel with the real-life trial conduct, we will performing Bayesian interim analyses according to the redesigned schedule as the trial proceeds, in real time. This will show whether the Bayesian adaptive design would lead to different conduct, results and conclusions from the conventional design. No results from these "shadow" analyses will be released until the trial has concluded.