Population pharmacokinetic-pharmacodynamic modeling and model-based prediction of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer.

PURPOSE: Docetaxel is used to treat many cancers, and neutropenia is the dose-limiting factor for its clinical use. A population pharmacokinetic-pharmacodynamic (PK-PD) model was introduced to predict the development of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer (NSCLC).

METHODS: Forty-seven advanced or recurrent Japanese patients with NSCLC were enrolled. Patients received 50 or 60 mg/m(2) docetaxel as monotherapy, and blood samples for a PK analysis were collected up to 24 h after its infusion. Laboratory tests including absolute neutrophil count data and demographic information were used in population PK-PD modeling. The model was built by NONMEM 7.2 with a first-order conditional estimation using an interaction method. Based on the final model, a Monte Carlo simulation was performed to assess the impact of covariates on and the predictability of neutropenia.

RESULTS: A three-compartment model was employed to describe PK data, and the PK model adequately described the docetaxel concentrations observed. Serum albumin (ALB) was detected as a covariate of clearance (CL): CL (L/h) = 32.5 × (ALB/3.6)(0.965) × (WGHT/70)(3/4). In population PK-PD modeling, a modified semi-mechanistic myelosuppression model was applied, and characterization of the time course of neutrophil counts was adequate. The covariate selection indicated that α1-acid glycoprotein (AAG) was a predictor of neutropenia. The model-based simulation also showed that ALB and AAG negatively correlated with the development of neutropenia and that the time course of neutrophil counts was predictable.

CONCLUSION: The developed model may facilitate the prediction and care of docetaxel-induced neutropenia.