DDMODEL00000048: Overall Survival model for Sunitinib Treatment in GIST

  public model
Short description:
A parametric time-to-event model, developed to explore the relationships between the four biomarkers, tumor size, and overall survival following sunitinib treatment in GIST.
Original code
  • PKPD Modeling of VEGF, sVEGFR-2, sVEGFR-3, and sKIT as Predictors of Tumor Dynamics and Overall Survival Following Sunitinib Treatment in GIST.
  • Hansson EK, Amantea MA, Westwood P, Milligan PA, Houk BE, French J, Karlsson MO, Friberg LE
  • CPT: pharmacometrics & systems pharmacology, 1/2013, Volume 2, pages: e84
  • Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
  • The predictive value of longitudinal biomarker data (vascular endothelial growth factor (VEGF), soluble VEGF receptor (sVEGFR)-2, sVEGFR-3, and soluble stem cell factor receptor (sKIT)) for tumor response and survival was assessed based on data from 303 patients with imatinib-resistant gastrointestinal stromal tumors (GIST) receiving sunitinib and/or placebo treatment. The longitudinal tumor size data were well characterized by a tumor growth inhibition model, which included, as significant descriptors of tumor size change, the model-predicted relative changes from baseline over time for sKIT (most significant) and sVEGFR-3, in addition to sunitinib exposure. Survival time was best described by a parametric time-to-event model with baseline tumor size and relative change in sVEGFR-3 over time as predictive factors. Based on the proposed modeling framework to link longitudinal biomarker data with overall survival using pharmacokinetic-pharmacodynamic models, sVEGFR-3 demonstrated the greatest predictive potential for overall survival following sunitinib treatment in GIST.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e84; doi:10.1038/psp.2013.61; advance online publication 20 November 2013.
Sreenath M Krishnan
Context of model development: Risk & Benefit Characterization, Outcome Prediction (Clinical & design Viability); Variability sources in PK and PD (CYP, Renal, Biomarkers); Clinical end-point;
Long technical model description: Final PD model (predicting survival) of biomarker sVEGFR-3 and observed tumour baseline size during sunitinib treatment of imatinib-resistant GIST. 1 biomarker from BM included: sVEGFR-3. 3 compartments. 1st compartment: sVEGFR-3 timecourse. 2nd compartment: Weibull model for survival (including exponential dependent on sVEGFR-3 and tumour baseline). 3rd compartment: Weibull model for dropout. Patients with events (deaths) before first follow-up at 4 weeks are excluded. No tumour timecourse. PK model of sunitinib is not included in model; only posthoc CL. Covariate: Baseline tumour size observation. No IIV (1 dummy OMEGA/ETA fixed to 0). No residual error (one observation per individual and odd-type data). Estimation method: LAPLACE (+ COVARIANCE STEP).;
Model compliance with original publication: Yes;
Model implementation requiring submitter’s additional knowledge: No;
Modelling context description: Exploration of the relationships between the biomarkers, tumor size, and overall survival following sunitinib treatment in GIST; Survival modeling in GIST patients treated with Sunitinib.;
Modelling task in scope: simulation; estimation;
Nature of research: Clinical research & Therapeutic use;
Therapeutic/disease area: Oncology;
Annotations are correct.
This model is not certified.
  • Model owner: Sreenath M Krishnan
  • Submitted: Dec 15, 2015 12:44:23 PM
  • Last Modified: Jun 3, 2016 12:44:32 PM
Revisions
  • Version: 13 public model Download this version
    • Submitted on: Jun 3, 2016 12:44:32 PM
    • Submitted by: Sreenath M Krishnan
    • With comment: Updated model annotations.
  • Version: 12 public model Download this version
    • Submitted on: Jun 3, 2016 11:17:59 AM
    • Submitted by: Sreenath M Krishnan
    • With comment: Updated model annotations.
  • Version: 11 public model Download this version
    • Submitted on: Dec 15, 2015 12:44:23 PM
    • Submitted by: Sreenath M Krishnan
    • With comment: Edited model metadata online.
 
Help