4.5 Article

Practical implementation of the partial ordering continual reassessment method in a Phase I combination-schedule dose-finding trial

Journal

STATISTICS IN MEDICINE
Volume 41, Issue 30, Pages 5789-5809

Publisher

WILEY
DOI: 10.1002/sim.9594

Keywords

combination study; dose-finding; dose-schedule; partial ordering

Funding

  1. Merck
  2. National Institute for Health Research
  3. NIHR Cambridge Biomedical Research Centre
  4. Medical Research Council [MC_UU_00002/14]
  5. [NIHR-SRF-2015-08-001]
  6. [NIHR30057]
  7. [BRC-1215-20014]

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There is a growing medical interest in combining multiple drugs and optimizing dosing schedules in a single trial, but there are challenges in implementing advanced statistical methods. By sharing the experience of implementing a model-based partial ordering continual reassessment method (POCRM) design, the hope is to facilitate the uptake of more efficient methods in practice.
There is a growing medical interest in combining several agents and optimizing their dosing schedules in a single trial in order to optimize the treatment for patients. Evaluating at doses of several drugs and their scheduling in a single Phase I trial simultaneously possess a number of statistical challenges, and specialized methods to tackle these have been proposed in the literature. However, the uptake of these methods is slow and implementation examples of such advanced methods are still sparse to date. In this work, we share our experience of proposing a model-based partial ordering continual reassessment method (POCRM) design for three-dimensional dose-finding in an oncology trial. In the trial, doses of two agents and the dosing schedule of one of them can be escalated/de-escalated. We provide a step-by-step summary on how the POCRM design was implemented and communicated to the trial team. We proposed an approach to specify toxicity orderings and their a-priori probabilities, and developed a number of visualization tools to communicate the statistical properties of the design. The design evaluation included both a comprehensive simulation study and considerations of the individual trial behavior. The study is now enrolling patients. We hope that sharing our experience of the successful implementation of an advanced design in practice that went through evaluations of several health authorities will facilitate a better uptake of more efficient methods in practice.

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