https://osteobcn.files.wordpress.com/2012/04/enck.pdf

New Insights into the Placebo and Nocebo Responses

A framework for applying unfamiliar trial designs in studies of rare diseases.

Response-adaptive randomization has recently attracted a lot of attention in the literature. In this paper, we propose a new and simple family of response-adaptive randomization procedures that attain the Cramer--Rao lower bounds on the allocation variances for any allocation proportions, including optimal allocation proportions. The allocation probability functions of proposed procedures are discontinuous. The existing large sample theory for adaptive designs relies on Taylor expansions of the allocation probability functions, which do not apply to nondifferentiable cases. In the present paper, we study stopping times of stochastic processes to establish the asymptotic efficiency results. Furthermore, we demonstrate our proposal through examples, simulations and a discussion on the relationship with earlier works, including Efron's biased coin design.

Efficient randomized-adaptive designs

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.

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

Response-adaptive randomization for survival trials: the parametric approach

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.

Response‐Adaptive Randomization for Clinical Trials with Continuous Outcomes

Response-adaptive randomization in clinical trials uses accumulated patient response data to adjust the allocation probability for the next patient, so that a particular objective, for example, more patients assigned to the better performing treatment arm, can be achieved. This ethically appealing randomization procedure has gained significant attention in academia, regulatory agencies, and industry in light of widespread of adaptive clinical trial designs with the FDA’s Critical Path Initiative (FDA: Innovation or stagnation: challenge and opportunity on the critical path to new medical products, 2004). However, this procedure has also generated unmatched controversy since its first application in the ECMO trial (Bartlett et al., Pediatrics 76:479–487, 1985). In this chapter, we will describe response-adaptive randomization procedures from both frequentist and Bayesian perspectives and provide a comprehensive assessment on situations where such procedures should be applied.

Lanju Zhang

Papers

Response‐Adaptive Randomization for Clinical Trials with Continuous Outcomes

Response-Adaptive Randomization for Clinical Trials

Optimal Response-Adaptive Randomization for Clinical Trials