Abstract

625 Background: Although titrated-dose axitinib offers a good objective response rate (ORR) for metastatic renal cell carcinoma (RCC), its optimal initial dose is unclear because its dosing regimen is based on a hypertensive reaction. We investigated whether axitinib pharmacogenetics were related to clinical efficacy/adverse events, and calculated a model to predict clinical efficacy and adverse events, using pharmacokinetic data based on gene polymorphisms in a phase 2 trial. Methods: We prospectively evaluated objective response and adverse events to establish a prediction model in 44 consecutive patients with advanced RCC, treated with axitinib between October 2013 and March 2017. Gene polymorphisms, including ABC transporters ( BCRP and MDR1) and UGT1A were analyzed by whole-exome sequencing, Sanger sequencing, and DNA chips. To construct the prediction model for area under curve (AUC), we used an exponential regression model with gene polymorphisms and dosage as covariates. To further validate this prediction model, we prospectively compared the calculated AUC in this model with actual AUCs in 13 additional consecutive patients. Results: Actual AUC was significantly correlated with the best ORR ( P = 0.0002), and adverse events (grade 2–3 hand–foot syndrome [ P = 0.0055]; grade 2 hypothyroidism [ P = 0.0381]); it was also significantly correlated with calculated AUC ( P < 0.0001). Calculated AUC was also significantly associated with best ORR ( P = 0.0044), grade 2–3 hand–foot syndrome ( P = 0.0191) and grade 2 hypothyroidism ( P = 0.0082). Surprisingly, hypertension was associated with neither ORR nor AUC. In the validation study, calculated AUC before axitinib treatment precisely predicted actual AUC ( P = 0.0079) in 13 additional consecutive patients. Conclusions: Our pharmacogenetics-based AUC model may offer a more benign method to determine optimal initial axitinib doses than hypertension, and could contribute to more precise treatment of individuals with advanced RCC. Clinical trial information: UMIN000011147.

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