PURPOSE: Interpatient variability in the pharmacokinetics (PK) of cytarabine, etoposide, and daunorubicin following body surface area-adjusted doses calls for studies that point to other covariates to explain this variability. The purpose of this study was to investigate such relationships and give insights into the PK of this combination treatment. METHODS: A prospective population PK study of twenty-three patients with acute myeloid leukemia was undertaken. Plasma concentrations of patients were determined by high-pressure liquid chromatography. PK models were developed with NONMEM; for daunorubicin, PK information from a prior study was utilized. RESULTS: Baseline white blood cell count (bWBC) influenced the PK for all drugs. A small, statistically insignificant improvement in model fit was achieved when a relationship between bWBC and daunorubicin central volume of distribution was included. The volume increased 1.9% for each increase in bWBC by 1 × 10(6) cells/mL. The clearances of etoposide and cytarabine were significantly increased and decreased, respectively, by increased bWBC. Tenfold changes in bWBC were needed for these relationships to have potential clinical relevance. A decrease in creatinine clearance of 60 mL/min resulted in a decrease in etoposide clearance of 32%. CONCLUSIONS: Population-based models characterized the PK for all three drugs. bWBC was a significant covariate for etoposide and cytarabine and showed a trend for daunorubicin. Linking the significant bWBC relationships and the relationship between kidney function and etoposide clearance to clinical end points would support dose individualization. Patients with above-normal creatinine clearances and high bWBC may receive sub-optimal treatment due to elevated etoposide clearances.
PURPOSE: Interpatient variability in the pharmacokinetics (PK) of cytarabine, etoposide, and daunorubicin following body surface area-adjusted doses calls for studies that point to other covariates to explain this variability. The purpose of this study was to investigate such relationships and give insights into the PK of this combination treatment. METHODS: A prospective population PK study of twenty-three patients with acute myeloid leukemia was undertaken. Plasma concentrations of patients were determined by high-pressure liquid chromatography. PK models were developed with NONMEM; for daunorubicin, PK information from a prior study was utilized. RESULTS: Baseline white blood cell count (bWBC) influenced the PK for all drugs. A small, statistically insignificant improvement in model fit was achieved when a relationship between bWBC and daunorubicin central volume of distribution was included. The volume increased 1.9% for each increase in bWBC by 1 × 10(6) cells/mL. The clearances of etoposide and cytarabine were significantly increased and decreased, respectively, by increased bWBC. Tenfold changes in bWBC were needed for these relationships to have potential clinical relevance. A decrease in creatinine clearance of 60 mL/min resulted in a decrease in etoposide clearance of 32%. CONCLUSIONS: Population-based models characterized the PK for all three drugs. bWBC was a significant covariate for etoposide and cytarabine and showed a trend for daunorubicin. Linking the significant bWBC relationships and the relationship between kidney function and etoposide clearance to clinical end points would support dose individualization. Patients with above-normal creatinine clearances and high bWBC may receive sub-optimal treatment due to elevated etoposide clearances.
Authors: Mina Nikanjam; Edmund V Capparelli; Jeffrey E Lancet; Arthur Louie; Gary Schiller Journal: Cancer Chemother Pharmacol Date: 2017-11-22 Impact factor: 3.333
Authors: Mohamed Elmeliegy; Jason Den Haese; Chetasi Talati; Meir Wetzler; William J Jusko Journal: Cancer Chemother Pharmacol Date: 2020-08-03 Impact factor: 3.333
Authors: Patrick D Halley; Christopher R Lucas; Emily M McWilliams; Matthew J Webber; Randy A Patton; Comert Kural; David M Lucas; John C Byrd; Carlos E Castro Journal: Small Date: 2015-11-19 Impact factor: 13.281