AIMS: To assess quantitatively the safety and pharmacology of paclitaxel in patients with moderate to severe hepatic impairment. METHODS: Solid tumour patients were enrolled into five liver function cohorts as defined by liver transaminase and total bilirubin concentrations. Paclitaxel was administered as a 3-h intravenous infusion at doses ranging from 110 to 175 mg m(-2), depending on liver impairment. Covariate and semimechanistic pharmacokinetic-pharmacodynamic (PK-PD) population modelling was used to describe the impact of liver impairment on the pharmacology and safety of paclitaxel. RESULTS: Thirty-five patients were included in the study, and PK data were assessed for 59 treatment courses. Most patients had advanced breast cancer (n = 22). Objective responses to paclitaxel were seen in four patients (11%). Patients in higher categories of liver impairment had a significantly lower paclitaxel elimination capacity (R2 = -0.38, P = 0.05), and total bilirubin was a significant covariate to predict decreased elimination capacity with population modelling (P = 0.002). Total bilirubin was also a significant predictor of increased haematological toxicity within the integrated population PK-PD model (P < 10(-4)). Data simulations were used to calculate safe initial paclitaxel doses, which were lower than the administered doses for liver impairment cohorts III-V. CONCLUSIONS: Total bilirubin is a good predictor of paclitaxel elimination capacity and of individual susceptibility to paclitaxel-related myelosuppression in cancer patients with moderate to severe liver impairment. The proposed, adapted paclitaxel doses need validation in prospective trials.
AIMS: To assess quantitatively the safety and pharmacology of paclitaxel in patients with moderate to severe hepatic impairment. METHODS: Solid tumourpatients were enrolled into five liver function cohorts as defined by liver transaminase and total bilirubin concentrations. Paclitaxel was administered as a 3-h intravenous infusion at doses ranging from 110 to 175 mg m(-2), depending on liver impairment. Covariate and semimechanistic pharmacokinetic-pharmacodynamic (PK-PD) population modelling was used to describe the impact of liver impairment on the pharmacology and safety of paclitaxel. RESULTS: Thirty-five patients were included in the study, and PK data were assessed for 59 treatment courses. Most patients had advanced breast cancer (n = 22). Objective responses to paclitaxel were seen in four patients (11%). Patients in higher categories of liver impairment had a significantly lower paclitaxel elimination capacity (R2 = -0.38, P = 0.05), and total bilirubin was a significant covariate to predict decreased elimination capacity with population modelling (P = 0.002). Total bilirubin was also a significant predictor of increased haematological toxicity within the integrated population PK-PD model (P < 10(-4)). Data simulations were used to calculate safe initial paclitaxel doses, which were lower than the administered doses for liver impairment cohorts III-V. CONCLUSIONS: Total bilirubin is a good predictor of paclitaxel elimination capacity and of individual susceptibility to paclitaxel-related myelosuppression in cancerpatients with moderate to severe liver impairment. The proposed, adapted paclitaxel doses need validation in prospective trials.
Authors: Markus Joerger; Alwin D R Huitema; Desiree H J G van den Bongard; Jan H M Schellens; Jos H Beijnen Journal: Clin Cancer Res Date: 2006-04-01 Impact factor: 12.531
Authors: A Henningsson; A Sparreboom; M Sandström; A Freijs; R Larsson; J Bergh; P Nygren; M O Karlsson Journal: Eur J Cancer Date: 2003-05 Impact factor: 9.162
Authors: W H Wilson; S L Berg; G Bryant; R E Wittes; S Bates; A Fojo; S M Steinberg; B R Goldspiel; J Herdt; J O'Shaughnessy Journal: J Clin Oncol Date: 1994-08 Impact factor: 44.544
Authors: E A Eisenhauer; W W ten Bokkel Huinink; K D Swenerton; L Gianni; J Myles; M E van der Burg; I Kerr; J B Vermorken; K Buser; N Colombo Journal: J Clin Oncol Date: 1994-12 Impact factor: 44.544
Authors: M T Huizing; A C Keung; H Rosing; V van der Kuij; W W ten Bokkel Huinink; I M Mandjes; A C Dubbelman; H M Pinedo; J H Beijnen Journal: J Clin Oncol Date: 1993-11 Impact factor: 44.544
Authors: Markus Joerger; Andrés J M Ferreri; Stephan Krähenbühl; Jan H M Schellens; Thomas Cerny; Emanuele Zucca; Alwin D R Huitema Journal: Br J Clin Pharmacol Date: 2012-02 Impact factor: 4.335
Authors: Markus Joerger; Stefanie Kraff; Alwin D R Huitema; Gary Feiss; Berta Moritz; Jan H M Schellens; Jos H Beijnen; Ulrich Jaehde Journal: Clin Pharmacokinet Date: 2012-09-01 Impact factor: 6.447