uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
PKPD Modeling of Predictors for Side Effects and Overall Survival in Sunitinb Treated Patients with Gastro Intestinal Stromal Tumor
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Research Group)
(Pfizer Global Research and Development)
(Pfizer Global Research and Development)
(Pfizer Global Research and Development)
Show others and affiliations
(English)Manuscript (preprint) (Other academic)
National Category
Cancer and Oncology
URN: urn:nbn:se:uu:diva-170737OAI: oai:DiVA.org:uu-170737DiVA: diva2:509449
Available from: 2012-03-12 Created: 2012-03-12 Last updated: 2012-04-19
In thesis
1. Pharmacometric Models for Biomarkers, Side Effects and Efficacy in Anticancer Drug Therapy
Open this publication in new window or tab >>Pharmacometric Models for Biomarkers, Side Effects and Efficacy in Anticancer Drug Therapy
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

New approaches quantifying the effect of treatment are needed in oncology to improve the drug development process and to enable treatment optimization for existing therapies. This thesis focuses on the development of pharmacometric models for biomarkers, side effects and efficacy in order to identify predictors of clinical response in anti-cancer drug therapy.

The variability in myelosuppression was characterized in six different cytotoxic anticancer treatments to evaluate a model-based dose individualization approach utilizing neutrophil counts as a biomarker. The estimated impact of inter-occasion variability was relatively low in relation to the inter-individual variability, indicating that myelosuppression is predictable from one treatment course to another. The approach may thereby be useful for dose optimization within an individual.

To further study and to identify predictors for the severe side effect febrile neutropenia (FN), the relationship between the shape of the myelosuppression time-course and the probability of FN was characterized. Patients with a rapid decline in neutrophil counts and high drug sensitivity were identified to have a higher probability of developing FN compared with other patients who experience grade 4 neutropenia.

Predictors of clinical response in patients receiving sunitinib for the treatment of gastro-intestinal stromal tumor (GIST) were identified by the development of an integrated modeling framework. Drug exposure, biomarkers, tumor dynamics, side effects and overall survival (OS) were linked in a unified structure, and univariate and multivariate exposure variables were tested for their predictive capacities. The soluble biomarker, sVEGFR-3 and tumor size at start of treatment were found to be promising predictors of overall survival, with decreased sVEGFR-3 levels and smaller baseline tumor size being predictive of longer OS. Also hypertension and neutropenia was identified as predictors of OS. The developed modeling framework may be useful to monitor clinical response, optimize dosing in sunitinib and to facilitate dose individualization.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2012. 58 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 157
Pharmacokinetics, Pharmacodynamics, Oncology, Febrile Neutropenia, GIST, Sunitinib
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
urn:nbn:se:uu:diva-170738 (URN)978-91-554-8312-8 (ISBN)
Public defence
2012-05-04, B42, Uppsala Biomedical Center, Husargatan 3, Uppsala, 13:15 (English)
Available from: 2012-04-13 Created: 2012-03-12 Last updated: 2012-04-19Bibliographically approved

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Hansson, EmmaFriberg, Lena
By organisation
Department of Pharmaceutical Biosciences
Cancer and Oncology

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 177 hits
ReferencesLink to record
Permanent link

Direct link