Evaluation of a pharmacology-driven dosing algorithm of 3-weekly paclitaxel using therapeutic drug monitoring: a pharmacokinetic-pharmacodynamic simulation study.
OBJECTIVE
Severe neutropenia is the most frequent and important toxicity of 3-weekly paclitaxel and puts patients at substantial risk of infectious complications. It is well known that the time during which paclitaxel plasma concentrations exceed 0.05 μmol/L (T(C>0.05)) correlates with the extent of neutropenia. This study was initiated to develop a dosing algorithm that would be able to reduce severe neutropenia by targeting an individual paclitaxel T(C>0.05) between 26 and 31 hours, and could be validated in a prospective randomized trial by comparing it to conventional dosing of paclitaxel.


METHODS
Paclitaxel plasma concentration-time (n = 273) and absolute neutrophil count (ANC) data (152 of the 273 patients) were pooled from two previous studies and submitted to population pharmacokinetic and pharmacodynamic modelling using nonlinear mixed-effects modelling software NONMEM® version VII. To fit the data, we used a previously described 3-compartment model with saturable elimination and distribution, coupled to a semiphysiological model with a linear function to describe the myelotoxic effect of paclitaxel (E(paclitaxel)) on circulating neutrophils (neutropenia). Patient age, sex, body surface area (BSA), bilirubin and renal function were tested as potential covariates on the maximum elimination capacity of paclitaxel (VM(EL)). Limited sampling strategies were tested on the pharmacokinetic model for their accuracy to predict paclitaxel T(C>0.05). Subsequently, we proposed a first-cycle dosing algorithm that accounted for BSA, patient age and sex, while later cycles accounted for the previous-cycle paclitaxel T(C>0.05) (target: 26 to 31 hours) and ANC nadir to adapt the paclitaxel dose for the next treatment cycle. To test the adequacy of the proposed dosing algorithm, we used extensive data simulations on the final pharmacokinetic/pharmacodynamic model, generating datasets of 1000 patients for six subsequent treatment cycles. Grade 4 neutropenia was tested as a potential endpoint for a prospective clinical trial and simulated for two scenarios, i.e. conventional dosing of paclitaxel 200 mg/m(2) every 3 weeks, and personalized, pharmacology-driven dosing as outlined above.


RESULTS
Concentration-time data for paclitaxel were adequately described by the 3-compartment model. Also, individual ANC counts were adequately described by the semiphysiological model using a linear function to describe E(paclitaxel) on neutropenia. Patient age, sex, bilirubin and BSA were significant and independent covariates on the elimination of paclitaxel. Paclitaxel VM(EL) was 16% higher in males than in female patients, and a 10-year increase in age led to a 13% decrease in VM(EL). A single paclitaxel plasma concentration 24 hours after the start of infusion was adequate to predict paclitaxel T(C>0.05) (root squared mean error [RSME] = +0.5%), and the addition of an end-of-infusion sample did not further improve precision (RSME = -0.6%). Data simulations on the final pharmacokinetic/pharmacodynamic model and using the proposed dosing algorithm resulted in a first-cycle paclitaxel dose ranging from 150 to 185 mg/m(2) for women and from 165 to 200 mg/m(2) for men. Dose adaptations for cycles two to six ranged from -40% to +30%, with a final median paclitaxel dose of 167 mg/m(2) (range 76 to 311 mg/m(2)). When compared with conventional dosing (paclitaxel 200 mg/m(2) every 3 weeks), personalized dosing reduced grade 4 neutropenia in cycle one from 15% to 7%, and further to 4% in cycle 2.


CONCLUSIONS
This study proposes a pharmacology-driven dosing algorithm of 3-weekly paclitaxel to reduce the incidence of grade 4 neutropenia. A randomized clinical trial comparing this dosing algorithm with conventional BSA-based dosing of paclitaxel in patients with advanced non-small cell lung cancer is currently ongoing.
Department of Oncology & Hematology, Cantonal Hospital, St Gallen, Switzerland. markus.joerger@gmail.com
Markus
M
Joerger
Stefanie
S
Kraff
Alwin D R
AD
Huitema
Gary
G
Feiss
Berta
B
Moritz
Jan H M
JH
Schellens
Jos H
JH
Beijnen
Ulrich
U
Jaehde
D000368:Aged; D000465:Algorithms; D000972:Antineoplastic Agents, Phytogenic / Q000008:administration & dosage / Q000493:pharmacokinetics*; D003198:Computer Simulation; D016903:Drug Monitoring; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy / Q000378:metabolism; D009503:Neutropenia / Q000139:chemically induced / Q000378:metabolism / Q000517:prevention & control; D017239:Paclitaxel / Q000008:administration & dosage / Q000493:pharmacokinetics*
D000972:Antineoplastic Agents, Phytogenic; D017239:Paclitaxel