A straightforward meta-analysis approach for oncology phase I dose-finding studies

Stat Med. 2022 Sep 10;41(20):3915-3940. doi: 10.1002/sim.9484. Epub 2022 Jun 5.

Abstract

Phase I early-phase clinical studies aim at investigating the safety and the underlying dose-toxicity relationship of a drug or combination. While little may still be known about the compound's properties, it is crucial to consider quantitative information available from any studies that may have been conducted previously on the same drug. A meta-analytic approach has the advantages of being able to properly account for between-study heterogeneity, and it may be readily extended to prediction or shrinkage applications. Here we propose a simple and robust two-stage approach for the estimation of maximum tolerated dose(s) utilizing penalized logistic regression and Bayesian random-effects meta-analysis methodology. Implementation is facilitated using standard R packages. The properties of the proposed methods are investigated in Monte Carlo simulations. The investigations are motivated and illustrated by two examples from oncology.

Keywords: Bayesian statistics; dose-escalation trial; random-effects meta-analysis; shrinkage estimation.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Computer Simulation
  • Dose-Response Relationship, Drug
  • Humans
  • Logistic Models
  • Maximum Tolerated Dose
  • Medical Oncology*
  • Monte Carlo Method
  • Research Design*