PKPD Modeling of VEGF, sVEGFR‐2, sVEGFR‐3, and sKIT as Predictors of Tumor Dynamics and Overall Survival Following Sunitinib Treatment in GIST

Abstract

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