2021/04/07 by Elja Arjas, Arjas, Elja, Dario Gasbarra +1 · 1 citation
Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Inference #Statistical Methods in Clinical Trials
paper · pdf · doi:10.48550/arxiv.2104.03398
openalex publication_date 2021/04/07 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Clinical trials are an instrument for making informed decisions based on evidence from well-designed experiments. Here we consider adaptive designs mainly from the perspective of multi-arm Phase II clinical trials, in which one or more experimental treatments are compared to a control. Treatment allocation of individual trial participants is assumed to take place according to a fixed block randomization, albeit with an important twist: The performance of each treatment arm is assessed after every measured outcome, in terms of the posterior distribution of a corresponding model parameter. Different treatments arms are then compared to each other, according to pre-defined criteria and using the joint posterior as the basis for such assessment. If a treatment is found to be sufficiently clearly inferior to the currently best candidate, it can be closed off either temporarily or permanently from further participant accrual. The latter possibility provides a method for adaptive treatment selection, including early stopping of the trial. The main development in the paper is in terms of binary outcomes, but some extensions, notably for handling time-to-event data, are discussed as well. The presentation is to a large extent comparative and expository.