Population pharmacokinetics and pharmacodynamics of paclitaxel and carboplatin in ovarian cancer patients: a study by the European organization for research and treatment of cancer-pharmacology and molecular mechanisms group and new drug development group.

Abstract

RESULTS

One hundred five patients had complete pharmacokinetic and toxicity data. In 34 patients with measurable disease, objective response rate was 76%. Neutrophil and thrombocyte counts were adequately described by an inhibitory linear response model. Paclitaxel t(C > 0.05) was significantly higher in patients with a complete (91.8 h) or partial (76.3 h) response compared with patients with progressive disease (31.5 h; P = 0.02 and 0.05, respectively). Patients with paclitaxel t(C > 0.05) > 61.4 h (mean value) had a longer time to disease progression compared with patients with paclitaxel t(C > 0.05) < 61.4 h (89.0 versus 61.9 weeks; P = 0.05). Paclitaxel t(C > 0.05) was a good predictor for severe neutropenia (P = 0.01), whereas carboplatin exposure (C(max) and area under the concentration-time curve) was the best predictor for thrombocytopenia (P < 10(-4)).

PURPOSE

Paclitaxel and carboplatin are frequently used in advanced ovarian cancer following cytoreductive surgery. Threshold models have been used to predict paclitaxel pharmacokinetic-pharmacodynamics, whereas the time above paclitaxel plasma concentration of 0.05 to 0.2 micromol/L (t(C > 0.05-0.2)) predicts neutropenia. The objective of this study was to build a population pharmacokinetic-pharmacodynamic model of paclitaxel/carboplatin in ovarian cancer patients.

CONCLUSIONS

In this group of patients, paclitaxel t(C > 0.05) is a good predictive marker for severe neutropenia and clinical outcome, whereas carboplatin exposure is a good predictive marker for thrombocytopenia.

EXPERIMENTAL DESIGN

One hundred thirty-nine ovarian cancer patients received paclitaxel (175 mg/m(2)) over 3 h followed by carboplatin area under the concentration-time curve 5 mg/mL*min over 30 min. Plasma concentration-time data were measured, and data were processed using nonlinear mixed-effect modeling. Semiphysiologic models with linear or sigmoidal maximum response and threshold models were adapted to the data.

More about this publication

Clinical cancer research : an official journal of the American Association for Cancer Research
  • Volume 13
  • Issue nr. 21
  • Pages 6410-8
  • Publication date 01-11-2007

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