6/10/2023 0 Comments Frequentist sequential testingFor trials that need an accelerated approval, group sequential designs offer an advantage over conventional designs by reducing the time to market. The relatively long follow-up time and recruiting period for assessing the primary outcome allow for the implementation of multiple interim analyses and opportunities for increasing efficiency. These designs have been widely implemented in large, long-term trials, such as phase III trials of drug development for fatal diseases, particularly where the endpoints were progression-free survival time and/or overall survival time. This design has the power to improve the efficiency of a clinical trial by reducing its duration without lowering any scientific and regulatory standards. Early termination for an efficacy trial can occur when the superiority of the treatment under study is established, for futility when the establishment of a relevant treatment difference is not likely, or for safety concerns when unacceptable adverse events become evident. These designs allow for multiple interim analyses at the data as the clinical trial proceeds and giving the possibility of stopping the trial early due to efficacy, futility, or safety reasons. These have been utilized for decades by the statistical and clinical trial communities. Sequential designs were extended to group sequential designs, in which patients are enrolled in successive groups instead of pairs. Sequential designs were first proposed by Armitage (1975) in which patients are recruited in pairs and the data analyzed as the results from each pair become available. The power of tests, the expected event size of the proposed design, and therefore the quality of estimators can be studied through simulations and this can be compared with the frequentist group sequential design. Also, a sensitivity analysis can be executed to evaluate the impact of different choices of prior parameters on choosing critical values. Bayes factor are often adapted for decision-making at interim analyses and present Algorithms to form decision rules and to calculate power of the proposed tests. Alpha spending function distributes the type I error over the duration of a sequential test. Bayesian sequential designs can be proposed for clinical trials with time-to-event outcomes and alpha spending functions are used to control the overall type I error rate. In a Bayesian trial, the prior information, and the trial results, as they emerge, are viewed as a continuous stream of information, in which inferences can be updated as new data become available. The increasing interest in Bayesian group sequential design is due to its potential to reinforce efficiency in clinical trials, shorten drug development time, and enhance the accuracy of statistical inference without compromising the integrity or validity of clinical trials.
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