DDMODEL00000222: Hansson_2013_Fatigue_GIST

  public model
Short description:
The model is a proportional odds models with a first-order Markov model for Fatigue. The model is based on 4 clinical studies in sunitinib treated GIST patients. Model comprised of files: Output_simulated_Fatigue_GIST.lst, Output_real_Fatigue_GIST.lst, Simulated_Fatigue_GIST.txt, Executable_Fatigue_GIST.mod, Command.txt
Original code
  • PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST.
  • Hansson EK, Ma G, Amantea MA, French J, Milligan PA, Friberg LE, Karlsson MO
  • CPT: pharmacometrics & systems pharmacology, 1/2013, Volume 2, pages: e85
  • Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
  • A modeling framework relating exposure, biomarkers (vascular endothelial growth factor (VEGF), soluble vascular endothelial growth factor receptor (sVEGFR)-2, -3, soluble stem cell factor receptor (sKIT)), and tumor growth to overall survival (OS) was extended to include adverse effects (myelosuppression, hypertension, fatigue, and hand-foot syndrome (HFS)). Longitudinal pharmacokinetic-pharmacodynamic models of sunitinib were developed based on data from 303 patients with gastrointestinal stromal tumor. Myelosuppression was characterized by a semiphysiological model and hypertension with an indirect response model. Proportional odds models with a first-order Markov model described the incidence and severity of fatigue and HFS. Relative change in sVEGFR-3 was the most effective predictor of the occurrence and severity of myelosuppression, fatigue, and HFS. Hypertension was correlated best with sunitinib exposure. Baseline tumor size, time courses of neutropenia, and relative increase of diastolic blood pressure were identified as predictors of OS. The framework has potential to be used for early monitoring of adverse effects and clinical response, thereby facilitating dose individualization to maximize OS.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e85; doi:10.1038/psp.2013.62; advance online publication 4 December 2013.
Pierrillas Philippe
Context of model development: Clinical end-point; Variability sources in PK and PD (CYP, Renal, Biomarkers);
Discrepancy between implemented model and original publication: None;
Long technical model description: Proportional odds models with a first-order Markov model for Fatigue in sunitinib treated GIST patients;
Model compliance with original publication: Yes;
Model implementation requiring submitter’s additional knowledge: No;
Modelling context description: Adverse effects may be useful alternative early indicators of pharmacodynamic activity as they could be more practical to use in the clinical setting;
Modelling task in scope: estimation;
Nature of research: Approval phase/Registration trial (Phase III); Early clinical development (Phases I and II);
Therapeutic/disease area: Oncology;
Annotations are correct.
This model is not certified.
  • Model owner: Pierrillas Philippe
  • Submitted: Oct 12, 2016 10:58:51 AM
  • Last Modified: Oct 12, 2016 10:58:51 AM
  • Version: 9 public model Download this version
    • Submitted on: Oct 12, 2016 10:58:51 AM
    • Submitted by: Pierrillas Philippe
    • With comment: Edited model metadata online.