Journal ArticleDOI
An optimal response-adaptive design with dual constraints
Atanu Biswas,Rahul Bhattacharya +1 more
TLDR
In this article, an optimal response-adaptive design for allocating patients among two competing treatments in a phase III clinical trial is presented, and an optimal target is developed for a general class of response distributions subject to two clinically relevant constraints.About:
This article is published in Statistics & Probability Letters.The article was published on 2010-02-01. It has received 7 citations till now.read more
Citations
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Journal ArticleDOI
Adaptive randomization for clinical trials.
TL;DR: 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.
Journal ArticleDOI
Response-adaptive designs for continuous treatment responses in phase III clinical trials: A review.
Atanu Biswas,Rahul Bhattacharya +1 more
TL;DR: This paper attempts to explore the available response-adaptive randomization procedures together with a comparison of their performances, and some real-life adaptive trial is reviewed.
Journal ArticleDOI
Doubly adaptive biased coin designs for balancing competing objectives in time-to-event trials
TL;DR: The doubly adaptive biased coin design of Hu and Zhang (2004) is implemented and its effectiveness is evaluated and it is shown that the proposed response-adaptive randomization designs generally outperform a balanced design when ethics, randomization and estimation efficiency are incorporated at the onset.
Journal ArticleDOI
Optimal response-adaptive allocation designs in phase III clinical trials: Incorporating ethics in optimality
Atanu Biswas,Rahul Bhattacharya +1 more
TL;DR: In this article, an optimal target for a general class of responses maintaining a prefixed lower bound for the allocation to the better treatment, in addition to an ensured level of statistical precision was obtained.
Posted Content
Response-adaptive randomization: an overview of designs and asymptotic theory
TL;DR: The authors provide an overview of important research works on response-adaptive randomization completed in the past decades, and provide a survey of the most relevant work in this area. But,
References
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Book
Nonlinear Programming: Theory and Algorithms
TL;DR: The book is a solid reference for professionals as well as a useful text for students in the fields of operations research, management science, industrial engineering, applied mathematics, and also in engineering disciplines that deal with analytical optimization techniques.
Journal ArticleDOI
Pregabalin for the treatment of postherpetic neuralgia A randomized, placebo-controlled trial
Robert H. Dworkin,Ann E. Corbin,J.P. Young,Uma Sharma,L. LaMoreaux,H. Bockbrader,E. A. Garofalo,R. M. Poole +7 more
TL;DR: Treatment of postherpetic neuralgia with pregabalin is safe, efficacious in relieving pain and sleep interference, and associated with greater global improvement than treatment with placebo.
Journal ArticleDOI
Optimal Adaptive Designs for Binary Response Trials
William F. Rosenberger,William F. Rosenberger,Nigel Stallard,Anastasia Ivanova,Cherice N. Harper,Michelle L. Ricks +5 more
TL;DR: It is found that the sequential procedure generally results in fewer treatment failures than the other procedures, particularly when the success probabilities of treatments are smaller.
Book
The Theory of Response-Adaptive Randomization in Clinical Trials
TL;DR: In this article, the authors present a general framework for response-adaptive randomization in clinical trials and prove the main theorems of the general framework in terms of power, probability, and asymptotic properties.
Journal ArticleDOI
Response‐Adaptive Randomization for Clinical Trials with Continuous Outcomes
TL;DR: An explicit asymptotic method is provided to evaluate the performance of different response-adaptive randomization procedures in clinical trials with continuous outcomes and concludes that the doubly adaptive biased coin design procedure targeting optimal allocation is the best one for practical use.