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Population pharmacokinetics and pharmacogenetics analyses of imatinib in Chinese patients with chronic myeloid leukemia in a real-world situation.
Cancer Chemotherapy and Pharmacology 2023 August 26
BACKGROUND: Imatinib is presently the first-line choice for the treatment of chronic myeloid leukemia. However, there are limited real-world data on Chinese patients to support individualized medicine. This work aims to characterize population pharmacokinetics in Chinese patients with chronic myeloid leukemia, investigate the effects of several covariates on imatinib exposure, and provide support for personalized medicine and dose reduction.
METHODS: A total of 230 patients with chronic myeloid leukemia were enrolled, and 424 steady-state concentration measurements were taken to perform the population pharmacokinetic analysis and Monte Carlo simulations with Phoenix NLME software. The effects of the demographic, biological, and pharmacogenetic (ten SNP corresponding to CYP3A4, CYP3A5, ABCB1, ABCG2, SCL22A1 and POR) covariates on clearance were evaluated.
RESULTS: A one-compartmental model best-described imatinib pharmacokinetics. The hemoglobin and the estimated glomerular filtration rate (< 85 mL⋅min-1 ⋅1.73 m2 ) were associated with imatinib clearance. The genetic polymorphisms related to pharmacokinetics were not found to have a significant effect on the clearance of imatinib. The final model estimates of parameters are: ka (h-1 ) = 0.329; Vd /F (L) = 270; CL/F (L⋅h-1 ) = 7.60.
CONCLUSIONS: Key covariates in the study population accounting for variability in imatinib exposure are hemoglobin and the estimated glomerular filtration rate. There is some need for caution when treating patients with moderate-to-severe renal impairment and significant hemoglobin changes.
METHODS: A total of 230 patients with chronic myeloid leukemia were enrolled, and 424 steady-state concentration measurements were taken to perform the population pharmacokinetic analysis and Monte Carlo simulations with Phoenix NLME software. The effects of the demographic, biological, and pharmacogenetic (ten SNP corresponding to CYP3A4, CYP3A5, ABCB1, ABCG2, SCL22A1 and POR) covariates on clearance were evaluated.
RESULTS: A one-compartmental model best-described imatinib pharmacokinetics. The hemoglobin and the estimated glomerular filtration rate (< 85 mL⋅min-1 ⋅1.73 m2 ) were associated with imatinib clearance. The genetic polymorphisms related to pharmacokinetics were not found to have a significant effect on the clearance of imatinib. The final model estimates of parameters are: ka (h-1 ) = 0.329; Vd /F (L) = 270; CL/F (L⋅h-1 ) = 7.60.
CONCLUSIONS: Key covariates in the study population accounting for variability in imatinib exposure are hemoglobin and the estimated glomerular filtration rate. There is some need for caution when treating patients with moderate-to-severe renal impairment and significant hemoglobin changes.
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