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A Knowledge Base of Designs and Statistical Methods for Adaptive Clinical Dose-Finding Trials.

Rob Kessels1, Yongxi Long2, Rene Spijker3

  • 1Julius Center for Health Sciences and Primary Care, Department of Data Science and Biostatistics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

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This literature review provides a knowledge base of adaptive clinical dose-finding trial designs and methods, focusing on oncology. It highlights recent advancements in identifying optimal doses considering toxicity and efficacy, and offers an interactive map to guide researchers.

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Pharmacology

Background:

  • Adaptive dose-finding trials are crucial for optimizing drug dosages in early-phase clinical studies.
  • A comprehensive overview of existing adaptive dose-finding trial methodologies is currently lacking.
  • Oncology has been a primary driver for the development of adaptive dose-finding trial designs.

Purpose of the Study:

  • To create a knowledge base of adaptive clinical dose-finding trial designs and statistical methods.
  • To systematically review and classify existing literature on adaptive dose-finding trials.
  • To facilitate the identification of suitable adaptive dose-finding designs for researchers.

Main Methods:

  • A comprehensive literature review was conducted, identifying 315 relevant articles.
  • Methodologies were classified based on design types (model-based, model-assisted, interval-based).
  • An interactive map was developed to categorize and summarize the reviewed designs and methods.

Main Results:

  • The majority of reviewed adaptive dose-finding trial methods were developed within the field of oncology.
  • Recent advancements focus on optimizing doses using both toxicity and efficacy, subgroup-specific finding, combination therapies, and delayed outcomes.
  • There is a notable shift from model-based designs (e.g., Continual Reassessment Method) towards model-assisted and interval-based designs (e.g., Toxicity Probability Interval, Bayesian Optimal Interval).

Conclusions:

  • The proliferation of adaptive dose-finding trial designs necessitates tools to aid researchers in selecting appropriate methods.
  • The interactive map serves as a valuable resource for navigating the diverse landscape of adaptive dose-finding trial methodologies.
  • Continued updates to the interactive map will ensure its relevance as new adaptive dose-finding trial designs emerge.