Early completion based on adjacent dose information for model-assisted designs to accelerate maximum tolerated dose finding
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Masahiro Kojima
Abstract
Phase I trials aim to identify the maximum tolerated dose (MTD) early and proceed quickly to an expansion cohort or a Phase II trial to assess the efficacy of the treatment. We present an early completion method based on multiple dosages (adjacent dose information) to accelerate the identification of the MTD in model-assisted designs. By using not only toxicity data for the current dose but also toxicity data for the next higher and lower doses, the MTD can be identified early without compromising accuracy. The early completion method is performed based on dose-assignment probabilities for multiple dosages. These probabilities are straightforward to calculate. We evaluated the early completion method using from an actual clinical trial. In a simulation study, we evaluated the percentage of correct MTD selection and the impact of early completion on trial outcomes. The results indicate that our proposed early completion method maintains a high level of accuracy in MTD selection, with minimal reduction compared to the standard approach. In certain scenarios, the accuracy of MTD selection even improves under the early completion framework. We conclude that the use of this early completion method poses no issue when applied to model-assisted designs.
Acknowledgments
The author is grateful to the editor, associate editor, and reviewer for their valuable comments and helpful suggestions. The author thanks Professor Hisashi Noma for his encouragement and helpful suggestions.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: MK.
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Use of Large Language Models, AI and Machine Learning Tools: ChatGPT proofed our manuscript.
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Conflict of interest: Not applicable.
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Research funding: Not applicable.
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Data availability: Not applicable.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/ijb-2023-0040).
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