Non-parametric overdose control for dose finding in drug combination trials

Chi Kin Lam, Ruitao Lin, Guosheng Yin

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

With the emergence of novel targeted anticancer agents, drug combinations have been recognized as cutting edge development in oncology. However, limited attention has been paid to overdose control in the existing drug combination dose finding methods which simultaneously find a set of maximum tolerated dose (MTD) combinations. To enhance patient safety, we develop the multiple-agent non-parametric overdose control (MANOC) design for identifying the MTD combination in phase I drug combination trials. By minimizing an asymmetric loss function, we control the probability of overdosing in a local region of the current dose combination. We further extend the MANOC design to identify the MTD contour by conducting a sequence of single-agent subtrials with the dose level of one agent fixed. Simulation studies are conducted to investigate the performance of the designs proposed. Although the MANOC design can prevent patients from being allocated to overtoxic dose levels, its accuracy and efficiency in dose finding remain competitive with existing methods. As an illustration, the MANOC design is applied to a phase I clinical trial for identifying the MTD combinations of buparlisib and trametinib.

Original languageEnglish
Pages (from-to)1111-1130
Number of pages20
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume68
Issue number4
DOIs
Publication statusPublished - Aug 2019
Externally publishedYes

Keywords

  • Bayesian model selection
  • Drug combination
  • Loss function
  • Maximum tolerated dose contour
  • Non-parametric design

Fingerprint

Dive into the research topics of 'Non-parametric overdose control for dose finding in drug combination trials'. Together they form a unique fingerprint.

Cite this