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Journal ArticleDOI

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

01 Aug 2011-Statistics & Probability Letters (North-Holland)-Vol. 81, Iss: 8, pp 1155-1160
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.
About: This article is published in Statistics & Probability Letters.The article was published on 2011-08-01. It has received 4 citations till now.
Citations
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Journal ArticleDOI
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.
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.

72 citations


Cites background from "Optimal response-adaptive allocatio..."

  • ...…et al., 2001; Ivanova and Rosenberger, 2001; Rosenberger and Hu, 2004; Baldi Antognini and Giovagnoli, 2010), normal outcomes (Biswas and Mandal, 2004; Zhang and Rosenberger, 2006; Gwise et al., 2008; Biswas and Bhattacharya, 2009, 2010, 2011), and survival outcomes (Zhang and Rosenberger, 2007)....

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Journal ArticleDOI
TL;DR: 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.

7 citations

Posted Content
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,
Abstract: In this paper we provide an overview of important research works on response-adaptive randomization completed in the past decades.

4 citations


Cites background from "Optimal response-adaptive allocatio..."

  • ...…Ivanova and Rosenberger (2001); Rosenberger and Hu (2004); Baldi Antognini and Giovagnoli (2010)), normal outcomes (Biswas and Mandal (2004); Zhang and Rosenberger (2006); Gwise, Hu and Hu (2008); Biswas and Bhattacharya (2009, 2010, 2011)), and survival outcomes (Zhang and Rosenberger (2007))....

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Journal ArticleDOI
TL;DR: An allocation function, invariant under monotonic transformation, is proposed in the context of multi-arm clinical trials for a class of continuous response distributions to skew the allocation towards the most promising treatment using the whole information about the response distributions.
Abstract: An allocation function, invariant under monotonic transformation, is proposed in the context of multi-arm clinical trials for a class of continuous response distributions. The aim is to skew the allocation towards the most promising treatment using the whole information about the response distributions. A response adaptive implementation based on the proposed allocation function is suggested and assessed through some useful performance measures.

1 citations


Cites background from "Optimal response-adaptive allocatio..."

  • ...total expected responses and total number of responses exceeding a clinically relevant threshold) a number of optimal allocation designs are developed [9, 10, 11, 12, 13, 14]....

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References
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Journal ArticleDOI
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.
Abstract: We derive the optimal allocation between two treatments in a clinical trial based on the following optimality criterion: for fixed variance of the test statistic, what allocation minimizes the expected number of treatment failures? A sequential design is described that leads asymptotically to the optimal allocation and is compared with the randomized play-the-winner rule, sequential Neyman allocation, and equal allocation at similar power levels. We find that the sequential procedure generally results in fewer treatment failures than the other procedures, particularly when the success probabilities of treatments are smaller.

242 citations

Book
18 Aug 2006
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.
Abstract: Dedication. Preface. 1. Introduction. 1.1 Randomization in clinical trials. 1.2 Response-adaptive randomization in a historical context. 1.3 Outline of the book. 1.4 References. 2. Fundamental Questions of response-Adaptive Randomization. 2.1 Optimal allocation. 2.2 The realtionship between power and response-adaptive randomization. 2.3 The relationship for K > 2 treatments. 2.4 Asymptotically best procedures. 2.5 References. 3. Likelihood-based Inference. 3.1 Data structure and Likelihood. 3.2 Asymptotic properties of maximum likelihood estimators. 3.4 Conclusion. 3.5 References. 4. Procedures Based on Urn Models. 4.1 Generalized Friedman's urn. 4.2 The class of ternary urn models. 4.3 References. 5. Procedures Based on Sequential Estimation. 5.1 Examples. 5.2 Properties of procedures based on sequential estimation for K = 2. 5.3 Notation and conditions for the general framework. 5.4 Asymptotic results and some examples. 5.5 Proving the main theorems. 5.6 References. 6. Sample Size Calculation. 6.1 Power of a randomization procedure. 6.2 Three types of sample size. 6.3 Examples. 6.4 References. 7. Additional Considerations. 7.1 The effect of delayed response. 7.2 Continuous responses. 7.3 Multiple (K > 2) treatments. 7.4 Accommodating heterogeneity. 7.5 References. 8. Implications for the Practice of Clinical Trials. 8.1 Standards. 8.2 Binary response. 8.3 Continuous responses. 8.4 The effect of delayed response. 8.5 Conclusions. 8.6 References. 9. Incorporating Covariates. 9.1 Introduction and examples. 9.2 General framework and asymptotic results. 9.3 Generalized linear models. 9.4 Two treatments with binary responses. 9.5 Conclusions. 9.6 References. 10. Conclusions and Open Problems. 10.1 Conclusions. 10.2 Open problems. 10.3 References. Appendix A: Supporting Technical Material. A.1 Some matrix theory. A.2 Jordan decomposition. A.3 Matrix recursions. A.4 Martingales. A.5 Cramer-Wold device. A.6 Multivariate martingales. A.7 Multivariate Taylor's expansion. A.8 References. Appendix B: Proofs. B.1 Proofs theorems in Chapter 4. B.2 Proof of theorems in Chapter 5. B.3 Proof of theorems in Chapter 7. B.4 References. Author Index. Subject Index.

222 citations

Journal ArticleDOI
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.
Abstract: We provide an explicit asymptotic method to evaluate the performance of different response-adaptive randomization procedures in clinical trials with continuous outcomes. We use this method to investigate four different response-adaptive randomization procedures. Their performance, especially in power and treatment assignment skewing to the better treatment, is thoroughly evaluated theoretically. These results are then verified by simulation. Our analysis concludes that the doubly adaptive biased coin design procedure targeting optimal allocation is the best one for practical use. We also consider the effect of delay in responses and nonstandard responses, for example, Cauchy distributed response. We illustrate our procedure by redesigning a real clinical trial.

103 citations

Journal Article
TL;DR: Of the three treatment modalities compared, conservative treatment without subsequent appendectomy appears to be the best.
Abstract: Background Appendiceal mass may be treated in several ways. However, no randomized trial has been conducted to find the best option. Objective To compare the three most commonly used methods for treating appendiceal mass. Methods Over a three-year period, 60 consecutive patients with appendiceal mass were randomly allocated to three groups: Group A--initial conservative treatment followed by interval appendectomy six weeks later; Group B--appendectomy as soon as appendiceal mass resolved using conservative means; Group C--conservative treatment alone. Short-term outcome measures included operative time, operative difficulty, postoperative complications, length of hospital stay, and duration of time away from work. Long-term outcome measures were: number of hospital visits made, presence of severe incisional pain, scar appearance, and patients with recurrent appendicitis. Results Baseline characteristics were comparable in the three groups. In patients in Group A, operative time was less, adhesions were encountered less frequently, the incision had to be extended less often and post-operative complications were fewer, as compared to Group B. Patients in Group C had the shortest hospital stay and duration of work-days lost; only 2 of 20 patients in this group developed recurrent appendicitis during a follow-up period of 24-52 (median 33.5) months. Conclusion Of the three treatment modalities compared, conservative treatment without subsequent appendectomy appears to be the best.

69 citations

Book ChapterDOI
01 Jan 2004
TL;DR: In this article, an optimal adaptive allocation for two treatments having some continuous responses was proposed for phase III clinical trials involving two binary responses having binary responses, but no covariate, where covariates were allowed in the model.
Abstract: Some optimal adaptive allocation design was given by (2002) for phase III clinical trials involving two treatments having binary responses, but no covariate We extend that idea to introduce an optimal adaptive allocation design for two treatments having some continuous responses Moreover, we allow covariates in our model Exact and limiting proportion of allocation for the proposed design are numerically evaluated

35 citations