Although axitinib is effective VEGF Tyrosine kinase inhibitor (TKI) for metastatic renal cell carcinoma (RCC), optimal initial dose remains unclear because dosing regimen relies to hypertension. We aimed to study if pharmaco-kinetic (PK) data has any relation to clinical efficacy/adverse event, and to establish the formulation of model that predict clinical efficacy and adverse events.
We prospectively evaluated the percent tumor reduction and adverse events in 40 patients (mean age: 66) treated with axitinib (median: 10mg/day) for advanced RCC (clear cell: 34, non-clear cell: 6). Gene polymorphisms of metabolic enzymes of axitinib (CYP3A4, UGT1A, ABCG2), and ABC transporter (BCRP, MDR-1) were analyzed using DNA chip, and PK data (AUC, total clearance, Cmax) were calculated from serum axitinib concentration measured by LC MS/MS. To construct the prediction model for PK data, exponential regression model was applied using 6 SNP data, with or without prior systemic therapies, and initial dose of axitinib as covariates.
Eleven of 34 evaluable patients (32%) had % tumor reduction >30% with a median of 13.5%. Major adverse events (Grade 3) were hypertension in 17 (43%), proteinuria in 7 (18%), respectively. Among several PK parameters, total clearance (CL-tot; dosage/AUC) was the most significantly associated with patient outcomes, i.e., reverse correlation with % reduction (R2 = 0.2542, p = 0.0017), and with proteinuria (p = 0.0058). There was a significant correlation between estimated CL-tot by prediction model and actual CL-tot (r2 = 0.6356, p
Estimated CL-tot may be more beneficial than hypertension to determine the optimal initial dose of axitinib in individual RCC patient.
Clinical trial identification
Legal entity responsible for the study
Institutional Review Board Yamaguchi University Hospital
Yamaguchi University Hospital Yamaguchi Prefecture
All authors have declared no conflicts of interest.