BACKGROUND: The aim of this study was to quantitatively assess the effect of anthropometric and biochemical variables and third-space effusions on paclitaxel pharmacokinetics in solid tumor patients. MATERIALS AND METHODS: Plasma concentration-time data of paclitaxel were collected in patients with non-small cell lung cancer (n = 84), ovarian cancer (n = 40), and various solid tumors (n = 44), totaling 168 patients. Paclitaxel was given as a 3-hour infusion (n = 163) at doses ranging from 100 to 250 mg/m(2), or as a 24-hour infusion (n = 5) at a dose of 135 or 175 mg/m(2). Data were analyzed using nonlinear mixed-effect modeling. RESULTS: A three-compartment model with saturable elimination and distribution was used to describe concentration-time data. Male gender and body surface area were positively correlated with maximal elimination capacity of paclitaxel (VM(EL)); patient age and total bilirubin were negatively correlated with VM(EL) (P < 0.005 for all correlations). Typically, male patients had a 20% higher VM(EL); a 0.2 m(2) increase of body surface area led to a 9% increase of VM(EL); a 10-year increase of patient age led to a 5% decrease of VM(EL); and a 10-micromol increase of total bilirubin led to a 14% decrease of VM(EL). Third-space effusions were not correlated with paclitaxel pharmacokinetics. CONCLUSIONS: This extended retrospective population analysis showed patient gender to significantly and independently affect paclitaxel distribution and elimination. Body surface area, total bilirubin, and patient age were confirmed to affect paclitaxel elimination. This pharmacokinetic model allowed quantification of the covariate effects on the elimination of paclitaxel and may be used for covariate-adapted paclitaxel dosing.
BACKGROUND: The aim of this study was to quantitatively assess the effect of anthropometric and biochemical variables and third-space effusions on paclitaxel pharmacokinetics in solid tumorpatients. MATERIALS AND METHODS: Plasma concentration-time data of paclitaxel were collected in patients with non-small cell lung cancer (n = 84), ovarian cancer (n = 40), and various solid tumors (n = 44), totaling 168 patients. Paclitaxel was given as a 3-hour infusion (n = 163) at doses ranging from 100 to 250 mg/m(2), or as a 24-hour infusion (n = 5) at a dose of 135 or 175 mg/m(2). Data were analyzed using nonlinear mixed-effect modeling. RESULTS: A three-compartment model with saturable elimination and distribution was used to describe concentration-time data. Male gender and body surface area were positively correlated with maximal elimination capacity of paclitaxel (VM(EL)); patient age and total bilirubin were negatively correlated with VM(EL) (P < 0.005 for all correlations). Typically, male patients had a 20% higher VM(EL); a 0.2 m(2) increase of body surface area led to a 9% increase of VM(EL); a 10-year increase of patient age led to a 5% decrease of VM(EL); and a 10-micromol increase of total bilirubin led to a 14% decrease of VM(EL). Third-space effusions were not correlated with paclitaxel pharmacokinetics. CONCLUSIONS: This extended retrospective population analysis showed patient gender to significantly and independently affect paclitaxel distribution and elimination. Body surface area, total bilirubin, and patient age were confirmed to affect paclitaxel elimination. This pharmacokinetic model allowed quantification of the covariate effects on the elimination of paclitaxel and may be used for covariate-adapted paclitaxel dosing.
Authors: Marie-Rose B S Crombag; Stijn L W Koolen; Sophie Wijngaard; Markus Joerger; Thomas P C Dorlo; Nielka P van Erp; Ron H J Mathijssen; Jos H Beijnen; Alwin D R Huitema Journal: Pharm Res Date: 2019-10-15 Impact factor: 4.200
Authors: Daniel L Hertz; Kelley M Kidwell; Kiran Vangipuram; Feng Li; Manjunath P Pai; Monika Burness; Jennifer J Griggs; Anne F Schott; Catherine Van Poznak; Daniel F Hayes; Ellen M Lavoie Smith; N Lynn Henry Journal: Clin Cancer Res Date: 2018-04-27 Impact factor: 12.531
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
Authors: Yongzhen Chen; Fang Fang; Kelley M Kidwell; Kiran Vangipuram; Lauren A Marcath; Christina L Gersch; James M Rae; Daniel F Hayes; Ellen M Lavoie Smith; N Lynn Henry; Andreas S Beutler; Daniel L Hertz Journal: Pharmacogenomics Date: 2020-07-23 Impact factor: 2.533
Authors: Lauren A Marcath; Kelley M Kidwell; Adam C Robinson; Kiran Vangipuram; Monika L Burness; Jennifer J Griggs; Catherine Van Poznak; Anne F Schott; Daniel F Hayes; Norah Lynn Henry; Daniel L Hertz Journal: Pharmacogenomics Date: 2018-12-06 Impact factor: 2.533
Authors: S D Baker; J Verweij; G A Cusatis; R H van Schaik; S Marsh; S J Orwick; R M Franke; S Hu; E G Schuetz; V Lamba; W A Messersmith; A C Wolff; M A Carducci; A Sparreboom Journal: Clin Pharmacol Ther Date: 2008-05-28 Impact factor: 6.875