Interpreting a Bayesian phase II futility clinical trial. 2022

Jonathan Beall, and Christy Cassarly, and Renee Martin
Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA. bealljo@musc.edu.

BACKGROUND A resurgence of research into phase II trial design in the mid-2000s led to the use of futility designs in a wide variety of disease areas. Phase II futility studies differ from efficacy studies in that their null hypothesis is that treatment, relative to control, does not meet or exceed the level of benefit required to justify additional study. A rejection of the null hypothesis indicates that the treatment should not proceed to a larger confirmatory trial. METHODS Bayesian approaches to the design of phase II futility clinical trials are presented and allow for the quantification of key probabilities, such as the predictive probability of current trial success or even the predictive probability of a future trial's success. RESULTS We provide an illustration of the design and interpretation of a phase II futility study constructed in a Bayesian framework. We focus on the operating characteristics of our motivating trial based on a simulation study, as well as the general interpretation of trial outcomes, type I, and type II errors in this framework. CONCLUSIONS Phase II futility clinical trials, when designed under in a Bayesian framework, offer an alternative approach to the design of mid-phase studies which provide unique benefits relative to trials designed in a frequentist framework and designs which focus on treatment efficacy.

UI MeSH Term Description Entries
D011336 Probability The study of chance processes or the relative frequency characterizing a chance process. Probabilities
D012107 Research Design A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly. Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D018447 Medical Futility The absence of a useful purpose or useful result in a diagnostic procedure or therapeutic intervention. The situation of a patient whose condition will not be improved by treatment or instances in which treatment preserves permanent unconsciousness or cannot end dependence on intensive medical care. (From Ann Intern Med 1990 Jun 15;112(12):949) Futile Treatment,Treatment Futility,Futility,Futility, Medical,Futile Treatments,Futility, Treatment,Treatment, Futile,Treatments, Futile

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