A practical Bayesian design to identify the maximum tolerated dose contour for drug combination trials

Liangcai Zhang, Ying Yuan

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

Drug combination therapy has become the mainstream approach to cancer treatment. One fundamental feature that makes combination trials different from single-agent trials is the existence of the maximum tolerated dose (MTD) contour, that is, multiple MTDs. As a result, unlike single-agent phase I trials, which aim to find a single MTD, it is often of interest to find the MTD contour for combination trials. We propose a new dose-finding design, the waterfall design, to find the MTD contour for drug combination trials. Taking the divide-and-conquer strategy, the waterfall design divides the task of finding the MTD contour into a sequence of one-dimensional dose-finding processes, known as subtrials. The subtrials are conducted sequentially in a certain order, such that the results of each subtrial will be used to inform the design of subsequent subtrials. Such information borrowing allows the waterfall design to explore the two-dimensional dose space efficiently using a limited sample size and decreases the chance of overdosing and underdosing patients. To accommodate the consideration that doses on the MTD contour may have very different efficacy or synergistic effects because of drug–drug interaction, we further extend our approach to a phase I/II design with the goal of finding the MTD with the highest efficacy. Simulation studies show that the waterfall design is safer and has higher probability of identifying the true MTD contour than some existing designs. The R package “BOIN” to implement the waterfall design is freely available from CRAN.

Original languageEnglish (US)
Pages (from-to)4924-4936
Number of pages13
JournalStatistics in Medicine
Volume35
Issue number27
DOIs
StatePublished - Nov 30 2016

Keywords

  • MTD contour
  • Phase I/II trial
  • bayesian adaptive design
  • dose-finding
  • drug combination

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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