A dose-finding design for phase I clinical trials based on Bayesian stochastic approximation.

ABSTRACT:

Background

Current dose-finding designs for phase I clinical trials can correctly select the MTD in a range of 30-80% depending on various conditions based on a sample of 30 subjects. However, there is still an unmet need for efficiency and cost saving.

Methods

We propose a novel dose-finding design based on Bayesian stochastic approximation. The design features utilization of dose level information through local adaptive modelling and free assumption of toxicity probabilities and hyper-parameters. It allows a flexible target toxicity rate and varying cohort size. And we extend it to accommodate historical information via prior effective sample size. We compare the proposed design to some commonly used methods in terms of accuracy and safety by simulation.

Results

On

SUBMITTER: Xu J 

PROVIDER: S-EPMC9526928 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature