Novel Clinical Trial Designs with Dose Optimization to Improve Long-term Outcomes

Author:

Thall Peter F.1ORCID,Zang Yong2ORCID,Chapple Andrew G.3ORCID,Yuan Ying1ORCID,Lin Ruitao1ORCID,Marin David4ORCID,Msaouel Pavlos567ORCID

Affiliation:

1. 1Department of Biostatistics, MD Anderson Cancer Center, Houston, Texas.

2. 2Department of Biostatistics and Health Data Science, Center for Computational Biology, and Bioinformatics, School of Medicine, Indiana University, Indianapolis, Indiana.

3. 3Department of Interdisciplinary Oncology, School of Medicine, LSU Health Sciences Center, New Orleans.

4. 4Department of Stem Cell Transplantation and Cellular Therapy, MD Anderson Cancer Center, Houston, Texas.

5. 5Department of Genitourinary Medical Oncology, MD Anderson Cancer Center, Houston, Texas.

6. 6Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.

7. 7David H. Koch Center for Applied Research of Genitourinary Cancers, The University of Texas MD Anderson Cancer Center, Houston, Texas.

Abstract

AbstractConventional designs for choosing a dose for a new therapy may select doses that are unsafe or ineffective and fail to optimize progression-free survival time, overall survival time, or response/remission duration. We explain and illustrate limitations of conventional dose-finding designs and make four recommendations to address these problems. When feasible, a dose-finding design should account for long-term outcomes, include screening rules that drop unsafe or ineffective doses, enroll an adequate sample size, and randomize patients among doses. As illustrations, we review three designs that include one or more of these features. The first illustration is a trial that randomized patients among two cell therapy doses and standard of care in a setting where it was assumed on biological grounds that dose toxicity and dose–response curves did not necessarily increase with cell dose. The second design generalizes phase I–II by first identifying a set of candidate doses, rather than one dose, randomizing additional patients among the candidates, and selecting an optimal dose to maximize progression-free survival over a longer follow-up period. The third design combines a phase I–II trial and a group sequential randomized phase III trial by using survival time data available after the first stage of phase III to reoptimize the dose selected in phase I–II. By incorporating one or more of the recommended features, these designs improve the likelihood that a selected dose or schedule will be optimal, and thus will benefit future patients and obtain regulatory approval.

Funder

National Institutes of Health

United States Department of Defense

Publisher

American Association for Cancer Research (AACR)

Subject

Cancer Research,Oncology

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