Open Access
2014 Adaptive clinical trial designs for phase I cancer studies
Oleksandr Sverdlov, Weng Kee Wong, Yevgen Ryeznik
Statist. Surv. 8: 2-44 (2014). DOI: 10.1214/14-SS106

Abstract

Adaptive clinical trials are becoming increasingly popular research designs for clinical investigation. Adaptive designs are particularly useful in phase I cancer studies where clinical data are scant and the goals are to assess the drug dose-toxicity profile and to determine the maximum tolerated dose while minimizing the number of study patients treated at suboptimal dose levels.

In the current work we give an overview of adaptive design methods for phase I cancer trials. We find that modern statistical literature is replete with novel adaptive designs that have clearly defined objectives and established statistical properties, and are shown to outperform conventional dose finding methods such as the 3+3 design, both in terms of statistical efficiency and in terms of minimizing the number of patients treated at highly toxic or nonefficacious doses. We discuss statistical, logistical, and regulatory aspects of these designs and present some links to non-commercial statistical software for implementing these methods in practice.

Citation

Download Citation

Oleksandr Sverdlov. Weng Kee Wong. Yevgen Ryeznik. "Adaptive clinical trial designs for phase I cancer studies." Statist. Surv. 8 2 - 44, 2014. https://doi.org/10.1214/14-SS106

Information

Published: 2014
First available in Project Euclid: 29 May 2014

zbMATH: 1295.82023
MathSciNet: MR3216028
Digital Object Identifier: 10.1214/14-SS106

Subjects:
Primary: 62L05 , 62L10 , 62L12
Secondary: 62L20

Keywords: “best intention” designs , Bayesian designs , continual reassessment method , dose finding studies , estimation efficiency , ethics , maximum tolerated dose , oncology trial designs , Optimal designs , phase I , stochastic approximation , toxicity , up-and-down designs

Rights: Copyright © 2014 The author, under a Creative Commons Attribution License

Vol.8 • 2014
Back to Top