Optimal Adaptive Designs in Phase III Clinical Trials for Continuous Responses with Covariates
01 Jan 2004-pp 51-59
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
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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
Cites background from "Optimal Adaptive Designs in Phase I..."
...Biswas and Mandal (2004) recently proposed a procedure that results in an allocation as a generalization of optimal allocation to normal responses....
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...Recently Biswas and Mandal (2004) generalized the binary optimal allocation for normal responses in terms of failures....
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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 Adaptive Designs in Phase I..."
..., 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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...…outcomes (Rosenberger 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…...
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TL;DR: In this paper, the optimal allocation approach and a parametric response-adaptive randomization procedure are used under exponential and Weibull distributions for survival outcomes and the asymptotic variance of the procedure is obtained for the exponential distribution.
Abstract: Summary Few references deal with response-adaptive randomization procedures for survival outcomes and those that do either dichotomize the outcomes or use a non-parametric approach In this paper, the optimal allocation approach and a parametric response-adaptive randomization procedure are used under exponential and Weibull distributions The optimal allocation proportions are derived for both distributions and the doubly adaptive biased coin design is applied to target the optimal allocations The asymptotic variance of the procedure is obtained for the exponential distribution The effect of intrinsic delay of survival outcomes is treated These findings are based on rigorous theory but are also verified by simulation It is shown that using a doubly adaptive biased coin design to target the optimal allocation proportion results in more patients being randomized to the better performing treatment without loss of power We illustrate our procedure by redesigning a clinical trial
63 citations
Cites methods from "Optimal Adaptive Designs in Phase I..."
...Others have developed response-adaptive randomization procedures that are suitable for the exponential model (e.g. Biswas and Mandal (2004))....
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...Many other procedures, such as those by Melfi et al. (2001) and Biswas and Mandal (2004), are a special case of this one....
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...Then we can minimize, as in Biswas and Mandal (2004), nA{1− exp.−c=θA/}+nB{1− exp.−c=θB/} and obtain the allocation proportion ρ= θA √ ["B{1− exp.−c=θB/}] θA √ ["B{1− exp.−c=θB/}]+θB√["A{1− exp.−c=θA/}] :...
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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.
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.
26 citations
TL;DR: The appropriate optimal response-adaptive design for normal or continuous distributions which provides the necessary correction for the ZR problem is provided.
Abstract: Most of the available response-adaptive designs in phase III clinical trial set up are not from any optimal consideration. An optimal design for binary responses is given by Rosenberger et al. (2001) and an optimal design for continuous responses is provided by Biswas and Mandal (2004). Recently, Zhang and Rosenberger (2006) [ZR] provided another design for normal responses. Biswas, Bhattacharya and Zhang (2007) pointed out that the design of ZR is not suitable for normally distributed responses, or any distribution having the possibility of negative mean, in general. But they only indicated the problem and bypassed the original problem and set up. In the present paper, we first start with the drawback of ZR. We then provide the appropriate optimal response-adaptive design for normal or continuous distributions which provides the necessary correction for the ZR problem. The proposed methods are illustrated using some real data.
22 citations
Cites methods from "Optimal Adaptive Designs in Phase I..."
...Biswas and Mandal (2004) [BM] provided a two-treatment response-adaptive design for continuous responses....
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...An optimal design for binary responses is given by Rosenberger et al. (2001) and an optimal design for continuous responses is provided by Biswas and Mandal (2004)....
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References
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