Emma K. Hansson (1), Guangli Ma (1,2), Michael Amantea (2), Jonathan French (2), Peter A. Milligan (2), Lena E. Friberg (1), Mats O. Karlsson (1)
(1) Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; (2) Pfizer Global Research and Development
Objectives: To describe the association between sunitinib exposure, candidate biomarkers (VEGF, sVEGFR-2, sVEGFR-3, sKIT) and side effects (myelosuppression, hypertension, fatigue and hand-foot syndrome) by the development of longitudinal pharmacokinetic-pharmacodynamic (PKPD) models. A further objective was to investigate relationships between side effects and overall survival (OS) in a model based analysis.
Methods: Neutropenia was well characterized by a semi-physiological model [2] and hypertension with an indirect response model [3]. Proportional odds models with a first order Markov model [3,4] described the time-course of the incidence and severity of fatigue and hand-foot syndrome (HFS). The relative change in sVEGFR-3 over time best described myelosuppression, fatigue and HFS. Hypertension was best predicted by sunitinib exposure. Baseline tumor size, neutropenia and the relative time-course of diastolic blood pressure (dBP) were identified as predictors of OS using a parametric time-to event model with a Weibull distribution.
Results: Neutropenia was well characterized by a semi-physiological model [2] and hypertension with an indirect response model [3]. Proportional odds models with a first order Markov model [3,4] described the time-course of the incidence and severity of fatigue and hand-foot syndrome (HFS). The relative change in sVEGFR-3 over time best described myelosuppression, fatigue and HFS. Hypertension was best predicted by sunitinib exposure. Baseline tumor size, neutropenia and the relative time-course of diastolic blood pressure (dBP) were identified as predictors of OS using a parametric time-to event model with a Weibull distribution.
Conclusions: The relative change in sVEGFR-3 over time was identified as a predictor of the occurrence and severity of myelosuppression, fatigue and HFS following sunitinib treatment. Furthermore, sunitinib induced elevation of dBP and neutropenia were identified as predictors of OS in GIST. The developed model has a potential to be used for early monitoring of treatment response thereby facilitating dose individualization.
References:
[1] Hansson et al. PAGE 20 (2011) Abstr 2183 [www.page-meeting.org/?abstract=2183].
2] Friberg LE et al. JCO 2002 Dec;20(24):4713-21.
[3] Keizer R et al. JPP. 2010;37(4):347-63.
[4] Zingmark et al. JPP 2005;32(2)261-81.
[5] Henin E et al. CPT 2009 Apr;85(4):418-25.
Reference: PAGE 21 () Abstr 2364 [www.page-meeting.org/?abstract=2364]
Poster: Oncology