mlsanityData to 13 Oct 2026

Dose-finding design based on level set estimation in phase I cancer clinical trials

arXiv 2504.09157 ↗First posted 12 Apr 2025stat.ML cs.LGcited by 0

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Abstract (arXiv)

The primary objective of phase I cancer clinical trials is to evaluate the safety of a new experimental treatment and to find the maximum tolerated dose (MTD). We show that the MTD estimation problem can be regarded as a level set estimation (LSE) problem whose objective is to determine the regions where an unknown function value is above or below a given threshold. Then, we propose a novel dose-finding design in the framework of LSE. The proposed design determines the next dose on the basis of an acquisition function incorporating uncertainty in the posterior distribution of the dose-toxicity curve as well as overdose control. Simulation experiments show that the proposed LSE design achieves a higher accuracy in estimating the MTD and involves a lower risk of overdosing allocation compared to existing designs, thereby indicating that it provides an effective methodology for phase I cancer clinical trial design.

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References · 6

  1. 2020On Information Gain and Regret Bounds in Gaussian Process Banditscited by 156
  2. 2020Corruption-Tolerant Gaussian Process Bandit Optimizationcited by 34
  3. 2019Bayesian optimisation under uncertain inputscited by 18
  4. 2022Look-Ahead Acquisition Functions for Bernoulli Level Set Estimationcited by 6
  5. 2021Adaptive Nonparametric Psychophysicscited by 5
  6. 2023Adaptive Defective Area Identification in Material Surface Using Active Transfer Learning-based Level Set Estimationcited by 4

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