Volume 36, Issue 2 p. 215-224
Special Issue Paper

Implementation of adaptive methods in early-phase clinical trials

Gina R. Petroni

Corresponding Author

Gina R. Petroni

Division of Translational Research and Applied Statistics, Department of Public Health Sciences, The University of Virginia, Charlottesville, VA, 22908 U.S.A.

Correspondence to: Petroni, Gina, Division of Translational Research and Applied Statistics, Department of Public Health Sciences, The University of Virginia, Charlottesville, VA 22908, U.S.A.

E-mail: [email protected]

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Nolan A. Wages

Nolan A. Wages

Division of Translational Research and Applied Statistics, Department of Public Health Sciences, The University of Virginia, Charlottesville, VA, 22908 U.S.A.

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Gautier Paux

Gautier Paux

Oncology Clinical Biostatistics, Institut de Recherches Internationales Servier (IRIS), Suresnes Cedex, 92284 France

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Frédéric Dubois

Frédéric Dubois

Oncology Clinical Biostatistics, Institut de Recherches Internationales Servier (IRIS), Suresnes Cedex, 92284 France

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First published: 29 February 2016
Citations: 26

Abstract

There has been constant development of novel statistical methods in the design of early-phase clinical trials since the introduction of model-based designs, yet the traditional or modified 3+3 algorithmic design remains the most widely used approach in dose-finding studies. Research has shown the limitations of this traditional design compared with more innovative approaches yet the use of these model-based designs remains infrequent. This can be attributed to several causes including a poor understanding from clinicians and reviewers into how the designs work, and how best to evaluate the appropriateness of a proposed design. These barriers are likely to be enhanced in the coming years as the recent paradigm of drug development involves a shift to more complex dose-finding problems. This article reviews relevant information that should be included in clinical trial protocols to aid in the acceptance and approval of novel methods. We provide practical guidance for implementing these efficient designs with the aim of augmenting a broader transition from algorithmic to adaptive model-guided designs. In addition we highlight issues to consider in the actual implementation of a trial once approval is obtained. Copyright © 2016 John Wiley & Sons, Ltd.

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