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

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.