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PKPD Modeling of VE...
PKPD Modeling of VEGF, sVEGFR-2, sVEGFR-3, and sKIT as Predictors of Tumor Dynamics and Overall Survival Following Sunitinib Treatment in GIST
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- Hansson, E K (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Pharmacometrics
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Amantea, M A (author)
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- Westwood, P (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Pharmacometrics
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Milligan, P A (author)
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Houk, B E (author)
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French, J (author)
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- Karlsson, Mats O (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Pharmacometrics
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- Friberg, Lena E (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Pharmacometrics
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(creator_code:org_t)
- 2013-11-20
- 2013
- English.
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In: CPT. - : Wiley. - 2163-8306. ; 2, s. e84-
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
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- 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.
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- art (subject category)
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