Adaptive group sequential designs for clinical trials: combining the advantages of adaptive and of classical group sequential approaches

A general method is presented integrating the concept of adaptive interim analyses into classical group sequential testing. This allows the researcher to represent every group sequential plan as an adaptive trial design and to make design changes during the course of the trial after every interim analysis in the same way as with adaptive designs. The concept of adaptive trial designing is thereby generalized to a large variety of possible sequential plans.     

A simple algorithm for designing group sequential clinical trials

This article describes a simple algorithm for calculating probabilities associated with group sequential trials. This allows the choice of boundaries that may not be among those implemented in available software.     

P-value adjustment in sequential clinical trials

Many randomized clinical trials utilize a group sequential monitoring procedure for assessing treatment efficacy during the course of the trial. For a group sequential trial in which the null hypothesis is ultimately rejected, the nominal p-value generally overstates the statistical significance of the result and some adjustment is required. Several orderings of the sample space have been proposed for performing this adjustment, each with unique operating characteristics. In this article, we compare four proposed methods with respect to the degree to which each captures the strength of evidence against the null hypothesis implied by the data. We conclude that the ordering of the sample space induced by the observed z-score has the most desirable operating characteristics.     

A group sequential type design for three‐arm non‐inferiority trials with binary endpoints

The three‐arm design with a test treatment, an active control and a placebo group is the gold standard design for non‐inferiority trials if it is ethically justifiable to expose patients to placebo. In this paper, we first use the closed testing principle to establish the hierarchical testing procedure for the multiple comparisons involved in the three‐arm design. For the effect preservation test we derive the explicit formula for the optimal allocation ratios. We propose a group sequential type design, which naturally accommodates the hierarchical testing procedure. Under this proposed design, Monte Carlo simulations are conducted to evaluate the performance of the sequential effect preservation test when the variance of the test statistic is estimated based on the restricted maximum likelihood estimators of the response rates under the null hypothesis. When there are uncertainties for the placebo response rate, the proposed design demonstrates better operating characteristics than the fixed sample design.     

Adaptive sample size calculations in group sequential trials

A method for group sequential trials that is based on the inverse normal method for combining the results of the separate stages is proposed. Without exaggerating the Type I error rate, this method enables data-driven sample size reassessments during the course of the study. It uses the stopping boundaries of the classical group sequential tests. Furthermore, exact test procedures may be derived for a wide range of applications. The procedure is compared with the classical designs in terms of power and expected sample size.