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- Joerger, Markus, et al.
(författare)
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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.
- 2007
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Ingår i: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 13:21, s. 6410-6418
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Tidskriftsartikel (refereegranskat)abstract
- 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 μmol/L (tC > 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. Experimental Design: One hundred thirty-nine ovarian cancer patients received paclitaxel (175 mg/m2) 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. 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 tC > 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 tC > 0.05 > 61.4 h (mean value) had a longer time to disease progression compared with patients with paclitaxel tC > 0.05 < 61.4 h (89.0 versus 61.9 weeks; P = 0.05). Paclitaxel tC > 0.05 was a good predictor for severe neutropenia (P = 0.01), whereas carboplatin exposure (Cmax and area under the concentration-time curve) was the best predictor for thrombocytopenia (P < 10−4). Conclusions: In this group of patients, paclitaxel tC > 0.05 is a good predictive marker for severe neutropenia and clinical outcome, whereas carboplatin exposure is a good predictive marker for thrombocytopenia.
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- Joerger, Markus, et al.
(författare)
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Population pharmacokinetics and pharmacodynamics of doxorubicin and cyclophosphamide in breast cancer patients : a study by the EORTC-PAMM-NDDG
- 2007
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Ingår i: Clinical Pharmacokinetics. - 0312-5963 .- 1179-1926. ; 46:12, s. 1051-1068
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Tidskriftsartikel (refereegranskat)abstract
- Aims: To investigate the population pharmacokinetics and pharmacodynamics of doxorubicin and cyclophosphamide in breast cancer patients. Patients and methods: Sixty-five female patients with early or advanced breast cancer received doxorubicin 60 mg/m(2) over 15 minutes followed by cyclophosphamide 600 mg/m(2) over 15 minutes. The plasma concentration-time data of both drugs were measured, and the relationship between drug pharmacokinetics and neutrophil counts was evaluated using nonlinear mixed-effect modelling. Relationships were explored between drug exposure (the area under the plasma concentration-time curve [AUC]), toxicity and tumour response. Results: Fifty-nine patients had complete pharmacokinetic and toxicity data. In 50 patients with measurable disease, the objective response rate was 60%, with complete responses in 6% of patients. Both doxorubicin and cyclophosphamide pharmacokinetics were associated with neutrophil toxicity. Cyclophosphamide exposure (the AUC) was significantly higher in patients with at least stable disease (n = 44) than in patients with progressive disease (n = 6; 945 mu mol . h/L [95% CI 889, 1001] vs 602 mu mol . h/L [95% CI 379, 825], p = 0.0002). No such correlation was found for doxorubicin. Body surface area was positively correlated with doxorubicin clearance; AST and patient age were negatively correlated with doxorubicin clearance; creatinine clearance was positively correlated with doxorubicinol clearance; and occasional concurrent use of carbamazepine was positively correlated with cyclophosphamide clearance. Conclusions: The proposed inhibitory population pharmacokinetic-pharmacodynamic model adequately described individual neutrophil counts after administration of doxorubicin and cyclophosphamide. In this patient population, exposure to cyclophosphamide, as assessed by the AUC, might have been a predictor of the treatment response, whereas exposure to doxorubicin was not. A prospective study should validate cyclophosphamide exposure as a predictive marker for the treatment response and clinical outcome in this patient group
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