GUIP1

GUIP1 implements model-guided adaptive dose-escalation methods to identify the maximum tolerated dose (MTD) in phase I cancer clinical trials.


Key Features:

  • Model-guided adaptive designs: Incorporates Continual Reassessment Method (CRM), Escalation with Overdose Control (EWOC), Time-to-Event Continual Reassessment Method (TITE-CRM), and Time-to-Event Escalation with Overdose Control (TITE-EWOC) for dose-toxicity modeling.
  • MTD definition: Targets estimation of the maximum tolerated dose (MTD), defined as the highest dose resulting in an acceptable level of severe toxicity during the first cycle of treatment.
  • CRM implementation: Implements CRM using Bayesian or maximum likelihood estimation and interfaces with R packages dfcrm and bcrm.
  • TITE-EWOC implementation: Includes a TITE-EWOC method developed within GUIP1 to address late-onset toxicity scenarios.
  • Simulation capability: Enables simulation of phase I clinical trials to assess model behavior and trial outcomes under specified scenarios.

Scientific Applications:

  • Phase I oncology dose escalation: Estimating the MTD for investigational therapies in phase I cancer clinical trials using adaptive model-based designs.
  • Toxicity management: Modeling and controlling immediate, cumulative, and late-onset toxicities during dose-escalation decisions.
  • Design evaluation: Simulating trial scenarios to compare performance of CRM, EWOC, TITE-CRM, and TITE-EWOC designs.

Methodology:

Implements CRM (Bayesian or maximum likelihood), EWOC, TITE-CRM, and a GUIP1-developed TITE-EWOC; CRM implementations leverage R packages dfcrm and bcrm and the package provides trial simulation functionality.

Topics

Details

Tool Type:
desktop application, library
Programming Languages:
R
Added:
1/18/2021
Last Updated:
1/30/2021

Operations

Publications

Dinart D, Fraisse J, Tosi D, Mauguen A, Touraine C, Gourgou S, Le Deley MC, Bellera C, Mollevi C. GUIP1: a R package for dose escalation strategies in phase I cancer clinical trials. BMC Medical Informatics and Decision Making. 2020;20(1). doi:10.1186/s12911-020-01149-3. PMID:32580715. PMCID:PMC7469913.

PMID: 32580715
PMCID: PMC7469913
Funding: - INCA: SHSESP-007