PKPD modeling of predictors for adverse effects and overall survival in sunitinib-treated patients with GIST

44Citations
Citations of this article
80Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

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. © 2013 ASCPT.

Cite

CITATION STYLE

APA

Ahansson, E. K., Ma, G., Amantea, M. A., French, J., Milligan, P. A., Friberg, L. E., & Karlsson, M. O. (2013). PKPD modeling of predictors for adverse effects and overall survival in sunitinib-treated patients with GIST. CPT: Pharmacometrics and Systems Pharmacology, 2(12). https://doi.org/10.1038/psp.2013.62

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free