Book ChapterDOI
An Overview of Adaptive Randomization Designs in Clinical Trials
Oleksandr Sverdlov
- pp 21-62
TLDR
In this article, a randomized, placebo-controlled, double-masked, equal-allocation clinical trial is presented, where the authors compare the effects of multiple treatments within multiple patient subgroups.Abstract:
Randomization Revisited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.4 Response-Adaptive Randomization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141.4.1 Response-Adaptive Randomized Urn Models . . . . . . . . . . . 14
1.4.2 Optimal Response-Adaptive Randomized Designs . . . . . 15
1.4.3 An Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.4.4 Bayesian Adaptive Randomization . . . . . . . . . . . . . . . . . . . . . . 19
1.4.5 Criticism of Response-AdaptiveRandomization Revisited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
1.5 Covariate-Adjusted Response-Adaptive Randomization . . . . . . . . 221.5.1 Treatment Effect Mapping and Urn-Based CARA
Randomization Designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231.5.2 Target-Based CARA Randomization Designs . . . . . . . . . . . 23
1.5.3 Utility-Based CARA Randomization Designs . . . . . . . . . . . 24
1.5.4 Bayesian CARA Randomization . . . . . . . . . . . . . . . . . . . . . . . . 241.6 Other Designs with Elements of Adaptive Randomization . . . . . . 25
1.6.1 Randomized Phase I Trial Designs . . . . . . . . . . . . . . . . . . . . . . 251.6.2 Adaptive Optimal Dose-Finding Designs . . . . . . . . . . . . . . . . 25
1.6.3 Randomized Designs with Treatment Selection . . . . . . . . . 26
1.6.4 Group Sequential Adaptive Randomization . . . . . . . . . . . . . 27
1.6.5 Complex Adaptive Design Strategies . . . . . . . . . . . . . . . . . . . . 281.7 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30A randomized, placebo-controlled, double-masked, equal-allocation clinical
trial can be viewed as an exemplary research design to obtain generalizable results on the treatment effect. However, modern clinical trials are increasingly
complex and often require more elaborate designs. A competitive landscape of
pharmaceutical research and development, an enormous number of molecules
that are available as potential drugs, and limited patient resources call for clinical trial designs investigating the effects of multiple treatments within multiple
patient subgroups. Such designs should, in addition, satisfy strict regulatory
requirements such as controlling the chance of making a type I error.read more
Citations
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Journal ArticleDOI
A response adaptive design for ordinal categorical responses.
TL;DR: A two treatment response adaptive design is developed for phase III clinical trials with ordinal categorical treatment outcome using Goodman-Kruskal measure of association.
Journal ArticleDOI
An adaptive allocation design for circular treatment outcome
TL;DR: In this article, the authors developed an allocation function in the context of circular treatment outcomes to assign a higher number of subjects to the treatment doing better in course of the trial, where the response is circular in nature, the definition of a better treatment differs from that under the linear response and hence the already developed designs lack appropriateness.
References
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Journal ArticleDOI
Optimum biased coin designs for sequential clinical trials with prognostic factors
TL;DR: In this paper, the authors used optimum design theory to provide a procedure of the biased coin type for an arbitrary number of treatments in the presence, or absence, of prognostic factors, and the results of the paper can be used for the sequential construction of DA-optimum designs in which randomization is not introduced by the experimenter.
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