4.6 Article

A Brief Overview of Adaptive Designs for Phase I Cancer Trials

期刊

CANCERS
卷 14, 期 6, 页码 -

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MDPI
DOI: 10.3390/cancers14061566

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phase I trial; cancer clinical trial; adaptive design; maximum tolerated dose; dose-limiting toxicity; nonparametric designs; algorithm-based designs; parametric model-based designs

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Phase I cancer trials play a crucial role in testing the safety and optimal dosage of new cancer drugs. Understanding biostatistical methodologies is essential for developing phase I studies that are safe and effective. This review article provides an overview of important phase I study designs and aims to help researchers better understand existing methods. Adaptive designs have shown significant advantages, and ongoing studies are continuously improving and developing new methods. This study provides a concise summary of dosage selection techniques for phase I cancer trials and presents various statistical designs.
Simple Summary Phase I cancer trials are important for new drug developments to test the safety and optimal dosage of cancer drugs which are usually toxic. Understanding biostatistical methodologies of these designs is important for developing phase I studies that are both safe for the participants and which use optimal dosages for better outcomes. Currently there are several phase I designs that are being refined and modified for better outcomes and newer designs are being continuously developed. In this review article, we described several important phase I study designs to provide a brief overview of existing methods. Our review could be helpful to the research community who intent to have a better and yet a concise summary of existing methods. Phase I studies are used to estimate the dose-toxicity profile of the drugs and to select appropriate doses for successive studies. However, literature on statistical methods used for phase I studies are extensive. The objective of this review is to provide a concise summary of existing and emerging techniques for selecting dosages that are appropriate for phase I cancer trials. Many advanced statistical studies have proposed novel and robust methods for adaptive designs that have shown significant advantages over conventional dose finding methods. An increasing number of phase I cancer trials use adaptive designs, particularly during the early phases of the study. In this review, we described nonparametric and algorithm-based designs such as traditional 3 + 3, accelerated titration, Bayesian algorithm-based design, up-and-down design, and isotonic design. In addition, we also described parametric model-based designs such as continual reassessment method, escalation with overdose control, and Bayesian decision theoretic and optimal design. Ongoing studies have been continuously focusing on improving and refining the existing models as well as developing newer methods. This study would help readers to assimilate core concepts and compare different phase I statistical methods under one banner. Nevertheless, other evolving methods require future reviews.

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