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Model-based Dose Individualization of Sunitinib in Gastrointestinal Stromal Tumors
- Publication Year :
- 2020
-
Abstract
- Purpose: Various biomarkers have been proposed for sunitinib therapy in gastrointestinal stromal tumor (GIST). However, the lack of "real-life" comparative studies hampers the selection of the most appropriate one. We, therefore, set up a pharmacometric simulation framework to compare each proposed biomarker. Experimental Design: Models describing relations between sunitinib exposure, adverse events (hand-foot syndrome, fatigue, hypertension, and neutropenia), soluble VEGFR (sVEGFR)-3, and overall survival (OS) were connected to evaluate the differences in survival and adverse events under different dosing algorithms. Various fixed dosing regimens [4/2 (weeks on/weeks off) or 2/1 (50 mg), and continuous daily dosing (37.5 mg)] and individualization approaches [concentration-adjusted dosing (CAD), toxicity-adjusted dosing (TAD), and sVEGFR-3-adjusted dosing (VAD)] were explored following earlier suggested blood sampling schedules and dose-reduction criteria. Model-based forecasts of biomarker changes were evaluated for predictive accuracy and the advantage of a model-based dosing algorithm was evaluated for clinical implementation. Results: The continuous daily dosing regimen was predicted to result in the longest survival. TAD (24.5 months) and VAD (25.5 months) increased median OS as compared with a fixed dose schedule (19.9 and 21.5 months, respectively) and CAD (19.7 and 21.3 months, respectively), without markedly raising the risk of intolerable toxicities. Changes in neutrophil count and sVEGFR-3 were accurately forecasted in the majority of subjects (> 65%), based on biweekly blood sampling. Conclusions: Dose adjustments based on the pharmacodynamic biomarkers neutrophil count and sVEGFR-3 can increase OS while retaining drug safety. Future efforts could explore the possibility of incorporating a model-based dose approach in clinical practice to increase dosing accuracy for these biomarkers.
Details
- Database :
- OAIster
- Notes :
- English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1235293742
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.1158.1078-0432.CCR-20-0887