Rahul Bhattacharya

Abstract: A variety of response-adaptive randomization procedures have been proposed in literature assuming binary outcomes. However, the list is not so long for continuous outcomes though many real clinical trials deal with continuous treatment responses. In this paper, we attempt to explore the available procedures together with a comparison of their performances. Some real-life adaptive trial is also reviewed.

Abstract: A randomized two-stage adaptive Bayesian design is proposed and studied for allocation and comparison in a phase III clinical trial with survival time as treatment response. Several exact and limiting properties of the design and the follow-up inference are studied, both numerically and theoretically, and are compared with a single-stage randomized procedure. The applicability of the proposed methodology is illustrated by using some real data.

Abstract: A randomized two-stage adaptive design is proposed and studied for allocation of patients to treatments and comparison in a phase III clinical trial with survival time as treatment responses. We consider the possibility of several covariates in the design and analysis. Several exact and limiting properties of the design and the follow-up inference are studied, both numerically and theoretically. The applicability of the proposed methodology is illustrated by using some real data.

Abstract: A randomized two-stage adaptive design is proposed and studied for allocation of patients to treatments and comparison in a phase III clinical trial with survival time as treatment responses. We consider the possibility of several covariates in the design and analysis. Several exact and limiting properties of the design and the follow-up inference are studied, both numerically and theoretically. The applicability of the proposed methodology is illustrated by using some real data.

Abstract: Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment. Optimal response-adaptive designs have become popular in recent days for this purpose, where the design is derived from some optimal viewpoints, mostly by optimizing some objective function subject to some constraint(s). However, most of the optimal designs are derived with two treatments and only a few works are available for several treatments. The present paper provides a generalized framework to derive multi-treatment optimal response-adaptive designs. A detailed performance study is provided for three treatment trials minimising failures. The applicability is also judged by redesigning some real clinical trials.

Abstract: (1976). Survival Distributions: Reliability Applications in the Biomedical Sciences. Technometrics: Vol. 18, No. 4, pp. 501-501.

Abstract: We propose a flexible method of extending a study based on conditional power. The possibility for extension when the p value at the planned end is small but not statistically significant is built in to the design of the study. The significance of the treatment difference at the planned end is used to determine the number of additional observations needed and the critical value necessary for use after accruing those additional observations. It may therefore be thought of as a two-stage procedure. Even though the observed treatment difference at stage 1 is used to make decisions, the Type I error rate is protected.

Abstract: In February 2010, the U.S. Food and Drug Administration (FDA, 2010) drafted guidance that discusses the statistical, clinical, and regulatory aspects of various adaptive designs for clinical trials. An important class of adaptive designs is adaptive randomization, which is considered very briefly in subsection VI.B of the guidance. The objective of this paper is to review several important new classes of adaptive randomization procedures and convey information on the recent developments in the literature on this topic. Much of this literature has been focused on the development of methodology to address past criticisms and concerns that have hindered the broader use of adaptive randomization. We conclude that adaptive randomization is a very broad area of experimental design that has important application in modern clinical trials.