ArticleFrontiers in pharmacology2025
Population pharmacokinetics of high-dose methotrexate in patients with primary central nervous system lymphoma.
Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Population pharmacokinetic model of high-dose methotrexate in Malaysian adults with hematological malignancies.European journal of clinical pharmacology · 2026Article
- Development and validation of high-dose methotrexate population pharmacokinetic models to inform clinical decisions on dosing.European journal of clinical pharmacology · 2026Article
- Risk factors associated with high-dose methotrexate induced toxicities in primary central nervous system lymphoma.Frontiers in pharmacology · 2025Article
- Population Pharmacokinetics and Covariate Analysis of Methotrexate in Pediatric Acute Lymphoblastic Leukemia.Drug design, development and therapy · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Methotrexate (MTX) serves as a cornerstone therapy for primary central nervous system lymphoma (PCNSL). However, the considerable intra- and inter-individual variability in its pharmacokinetic and therapeutic efficacy poses significant challenges to clinical application. This study aims to employ population pharmacokinetic (PPK) models to investigate the pharmacokinetics of MTX in Chinese patients with PCNSL, thereby facilitating personalized therapeutic strategies for these patients. Method: A retrospective dataset comprising 6074 MTX plasma concentrations from 752 adult patients with PCNSL receiving high-dose methotrexate (HD-MTX) therapy was employed to construct the PPK model, utilizing the nonlinear mixed-effects modeling approach. The pharmacokinetics of MTX were characterized using a three-compartment model in conjunction with a proportional residual model. Covariate effects on model parameters were evaluated using forward addition and backward elimination approaches. Model performance was assessed through goodness-of-fit, bootstrap analysis, and visual predictive checks. Result: In the final PPK models, the estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN), alanine aminotransferase (ALT), and a combined genotype of Conclusion: In managing HD-MTX therapy for PCNSL patients, it is essential to consider pharmacokinetic factors such as eGFR, BUN, ALT, TP, and genetic polymorphisms. The PPK models developed will aid in optimizing and personalizing HD-MTX treatment for PCNSL patients.
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