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Erschienen in:
01.04.2017 | Original Research Article
Population Pharmacokinetics of Intravenous Methotrexate in Patients with Hematological Malignancies: Utilization of Routine Clinical Monitoring Parameters
Erschienen in: European Journal of Drug Metabolism and Pharmacokinetics | Ausgabe 2/2017
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Background and Objective
Clinical response to methotrexate in cancer is variable and depends on several factors including serum drug exposure. This study aimed to develop a population pharmacokinetic model describing methotrexate disposition in cancer patients using retrospective chart review data available from routine clinical practice.
Methods
A retrospective review of medical records was conducted for cancer patients in Qatar. Relevant data (methotrexate dosing/concentrations from multiple occasions, patient history, and laboratory values) were extracted and analyzed using NONMEM VII®. A population pharmacokinetic model was developed and used to estimate inter-individual and inter-occasion variability terms on methotrexate pharmacokinetic parameters, as well as patient factors affecting methotrexate pharmacokinetics.
Results
Methotrexate disposition was described by a two-compartment model with clearance (CL) of 15.7 L/h and central volume of distribution (V
c) of 79.2 L. Patient weight and hematocrit levels were significant covariates on methotrexate V
c and CL, respectively. Methotrexate CL changed by 50 % with changes in hematocrit levels from 23 to 50 %. Inter-occasion variability in methotrexate CL was estimated for patients administered the drug on multiple occasions (48 and 31 % for 2nd and 3rd visits, respectively).
Conclusion
Therapeutic drug monitoring data collected during routine clinical practice can provide a useful tool for understanding factors affecting methotrexate pharmacokinetics. Patient weight and hematocrit levels may play a clinically important role in determining methotrexate serum exposure and dosing requirements. Future prospective studies are needed to validate results of the developed model and evaluate its usefulness to predict methotrexate exposure and optimize dosing regimens.