A population pharmacokinetic model for docetaxel (Taxotere): model building and validation

Abstract

A sparse sampling strategy (3 samples per patient, 521 patients) was implemented in 22 Phase 2 studies of docetaxel (Taxotere) at the first treatment cycle for a prospective population pharmacokinetic evaluation. In addition to the 521 Phase 2 patients, 26 (data rich) patients from Phase I studies were included in the analysis. NONMEM analysis of an index set of 280 patients demonstrated that docetaxel clearance (CL) is related to alpha 1-acid glycoprotein (AAG) level, hepatic function (HEP), age (AGE), and body surface area (BSA). The index set population model prediction of CL was compared to that of a naive predictor (NP) using a validation set of 267 patients. Qualitatively, the dependence of CL on AAG, AGE, BSA, and HEP seen in the index set population model was supported in the validation set. Quantitatively, for the validation set patients overall, the performance (bias, precision) of the model was good (7 and 21%, respectively), although not better than that of the NP. However, in all the subpopulations with decreased CL, the model performed better than the NP; the more the CL differed from the population average, the better the performance. For example, in the subpopulation of patients with AAG levels > 2.27 g/L (n = 26), bias and precision of model predictions were 24 and 32% vs. 53 and 53%, respectively, for the NP. The prediction of CL using the model was better (than that of the NP) in 73% of the patients. The population model was redetermined using the whole population of 547 patients and a new covariate, albumin plasma level, was found to be a significant predictor in addition to those found previously. In the final model, HEP, AAG, and BSA are the main predictors of docetaxel CL.