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PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST
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 (myelosuppre...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3868978/ https://www.ncbi.nlm.nih.gov/pubmed/24304978 http://dx.doi.org/10.1038/psp.2013.62 |
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author | Hansson, E K Ma, G Amantea, M A French, J Milligan, P A Friberg, L E Karlsson, M O |
author_facet | Hansson, E K Ma, G Amantea, M A French, J Milligan, P A Friberg, L E Karlsson, M O |
author_sort | Hansson, E K |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3868978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-38689782013-12-20 PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST Hansson, E K Ma, G Amantea, M A French, J Milligan, P A Friberg, L E Karlsson, M O CPT Pharmacometrics Syst Pharmacol Original Article 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. Nature Publishing Group 2013-12 2013-12-04 /pmc/articles/PMC3868978/ /pubmed/24304978 http://dx.doi.org/10.1038/psp.2013.62 Text en Copyright © 2013 American Society for Clinical Pharmacology and Therapeutics http://creativecommons.org/licenses/by-nc-nd/3.0/ CPT: Pharmacometrics and Systems Pharmacology is an open-access journal published by Nature Publishing Group. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Original Article Hansson, E K Ma, G Amantea, M A French, J Milligan, P A Friberg, L E Karlsson, M O PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST |
title | PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST |
title_full | PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST |
title_fullStr | PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST |
title_full_unstemmed | PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST |
title_short | PKPD Modeling of Predictors for Adverse Effects and Overall Survival in Sunitinib-Treated Patients With GIST |
title_sort | pkpd modeling of predictors for adverse effects and overall survival in sunitinib-treated patients with gist |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3868978/ https://www.ncbi.nlm.nih.gov/pubmed/24304978 http://dx.doi.org/10.1038/psp.2013.62 |
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