Exposure-Toxicity Association of Cyclophosphamide and Its Metabolites in Infants and Young Children with Primary Brain Tumors: Implications for Dosing

Abstract

Purpose: To characterize the population pharmacokinetics of cyclophosphamide, active 4-hydroxy-cyclophosphamide (4OH-CTX), and inactive carboxyethylphosphoramide mustard (CEPM), and their associations with hematologic toxicities in infants and young children with brain tumors. To use this information to provide cyclophosphamide dosing recommendations in this population.

Patients and methods: Patients received four cycles of a 1-hour infusion of 1.5 g/m² cyclophosphamide. Serial samples were collected to measure cyclophosphamide, 4OH-CTX, and CEPM plasma concentrations. Population pharmacokinetic modeling was performed to identify the patient characteristics influencing drug disposition. Associations between drug exposures and metrics reflecting drug-induced neutropenia, erythropenia, and thrombocytopenia were investigated. A Bayesian approach was developed to predict 4OH-CTX exposure using only cyclophosphamide and CEPM plasma concentrations.

Results: Data from 171 patients (0.07-4.9 years) were adequately fitted by a two-compartment (cyclophosphamide) and one-compartment model (metabolites). Young infants (<6 months) exhibited higher mean 4OH-CTX exposure than did young children (138.4 vs. 107.2 μmol/L·h, P < 0.0001). No genotypes exhibited clinically significant influence on drug exposures. Worse toxicity metrics were significantly associated with higher 4OH-CTX exposures. Dosing simulations suggested decreased cyclophosphamide dosage to 1.2 g/m² for young infants versus 1.5 g/m² for children to attain similar 4OH-CTX exposure. Bayesian-modeled 4OH-CTX exposure predictions were precise (mean absolute prediction error 14.8% ± 4.2%) and had low bias (mean prediction error 4.9% ± 5.1%).

Conclusions: A 4OH-CTX exposure-toxicity association was established, and a decreased cyclophosphamide dosage for young infants was suggested to reduce toxicity in this population. Bayesian modeling to predict 4OH-CTX exposure may reduce clinical processing-related costs and provide insights into further exposure-response associations.