T3 + 3: 3 + 3 Design With Delayed Outcomes

Author:

Guo Jiaying12,Lu Mengyi3,Wan Isabella4,Wang Yumin5,Han Leng16,Zang Yong16

Affiliation:

1. Department of Biostatistics and Health Data Science Indiana University Indianapolis Indiana USA

2. Eli Lilly and Company Indianapolis Indiana USA

3. Department of Biostatistics Nanjing Medical University Nanjing China

4. Faculty of Arts and Science University of Toronto Toronto Canada

5. Chengdu University Chengdu China

6. Center for Computational Biology and Bioinformatics Indiana University Indianapolis Indiana USA

Abstract

ABSTRACTDelayed outcome is common in phase I oncology clinical trials. It causes logistic difficulty, wastes resources, and prolongs the trial duration. This article investigates this issue and proposes the time‐to‐event 3 + 3 (T3 + 3) design, which utilizes the actual follow‐up time for at‐risk patients with pending toxicity outcomes. The T3 + 3 design allows continuous accrual without unnecessary trial suspension and is costless and implementable with pretabulated dose decision rules. Besides, the T3 + 3 design uses the isotonic regression to estimate the toxicity rates across dose levels and therefore can accommodate for any targeted toxicity rate for maximum tolerated dose (MTD). It dramatically facilitates the trial preparation and conduct without intensive computation and statistical consultation. The extension to other algorithm‐based phase I dose‐finding designs (e.g., i3 + 3 design) is also studied. Comprehensive computer simulation studies are conducted to investigate the performance of the T3 + 3 design under various dose‐toxicity scenarios. The results confirm that the T3 + 3 design substantially shortens the trial duration compared with the conventional 3 + 3 design and yields much higher accuracy in MTD identification than the rolling six design. In summary, the T3 + 3 design addresses the delayed outcome issue while keeping the desirable features of the 3 + 3 design, such as simplicity, transparency, and costless implementation. It has great potential to accelerate early‐phase drug development.

Funder

National Institutes of Health

Publisher

Wiley

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