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

Survival Distributions: Reliability Applications in the Biomedical Sciences

67A Designed extension of studies based on conditional power

Forcing a Sequential Experiment to be Balanced

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.

Adaptive randomization for clinical trials.

Adaptive or 'flexible' designs have emerged, mostly within frequentist frameworks, as an effective way to speed up the therapeutic evaluation process. Because of their flexibility, Bayesian methods have also been proposed for Phase I through Phase III adaptive trials; however, it has been reported that they are poorly used in practice. We aim to describe the international scientific production of Bayesian clinical trials by investigating the actual development and use of Bayesian 'adaptive' methods in the setting of clinical trials. A bibliometric study was conducted using the PubMed and Science Citation Index-Expanded databases. Most of the references found were biostatistical papers from various teams around the world. Most of the authors were from the US, and a large proportion was from the MD Anderson Cancer Center (University of Texas, Houston, TX). The spread and use of these articles depended heavily on their topic, with 3.1% of the biostatistical articles accumulating at least 25 citations within 5 years of their publication compared with 15% of the reviews and 32% of the clinical articles. We also examined the reasons for the limited use of Bayesian adaptive design methods in clinical trials and the areas of current and future research to address these challenges. Efforts to promote Bayesian approaches among statisticians and clinicians appear necessary.

Bayesian adaptive clinical trials: a dream for statisticians only?

Response-adaptive designs have become popular for allocation of the entering patients among two or more competing treatments in a phase III clinical trial. Although there are a lot of designs for binary treatment responses, the number of designs involving covariates is very small. Sometimes the patients give repeated responses. The only available response-adaptive allocation design for repeated binary responses is the urn design by Biswas and Dewanji [Biswas A and Dewanji AA. Randomized longitudinal play-the-winner design for repeated binary data. ANZJS 2004; 46: 675-684; Biswas A and Dewanji A. Inference for a RPW-type clinical trial with repeated monitoring for the treatment of rheumatoid arthritis. Biometr J 2004; 46: 769-779.], although it does not take care of the covariates of the patients in the allocation design. In this article, a covariate-adjusted response-adaptive randomisation procedure is developed using the log-odds ratio within the Bayesian framework for longitudinal binary responses. The small sample performance of the proposed allocation procedure is assessed through a simulation study. The proposed procedure is illustrated using some real data set.

Covariate-adjusted response-adaptive designs for longitudinal treatment responses: PEMF trial revisited.

An optimal response-adaptive design with dual constraints

An urn based covariate adjusted response adaptive allocation design with dichotomous responses is proposed incorporating the ordered nature of the covariate. The allocation procedure is assessed both numerically and theoretically. The performance of the allocation design is also investigated in a relevant hypothetical clinical trial.

Rahul Bhattacharya

Papers

Covariate-adjusted response-adaptive designs for longitudinal treatment responses: PEMF trial revisited.

An optimal response-adaptive design with dual constraints

An urn based covariate adjusted response adaptive allocation design

Optimal response-adaptive allocation designs in phase III clinical trials: Incorporating ethics in optimality

Response‐Adaptive Designs in Phase III Clinical Trials