ArticleCancer chemotherapy and pharmacology2024
An interactive dose optimizer based on population pharmacokinetic study to guide dosing of methotrexate in Chinese patients with osteosarcoma.
Article in Cancer chemotherapy and pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Development and validation of high-dose methotrexate population pharmacokinetic models to inform clinical decisions on dosing.European journal of clinical pharmacology · 2026Article
- Comparative Molecular Insights and Computational Modeling of Multiple Myeloma and Osteosarcoma.International journal of molecular sciences · 2026Review
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Authors and funding
9 authors.
Funding
Abstract
purposeOsteosarcoma is a rare tumor with an incidence of 4.4 cases per million per year in adolescent. High-dose methotrexate (HD-MTX) is the standard first-line chemotherapeutic agent for osteosarcoma. However, its efficacy can vary significantly among individuals due to wide pharmacokinetic variability. Despite this, only a few population pharmacokinetics (popPK) models based on Chinese patients with osteosarcoma have been reported. Thus, this study aimed to develop a HD-MTX popPK model and an individual model-based dose optimizer for osteosarcoma therapy.
methodA total of 680 MTX serum concentrations from 57 patients with osteosarcoma were measured at the end of MTX infusion and 10 h, 24 h, 48 h, and 72 h after the start of infusion. Using the first-order conditional estimation method with NONMEM, a popPK model was estimated. Goodness-of-fit plots, visual predictive checks, and bootstrap analysis were generated to evaluate the final model. A dose optimizer tool was developed based on the validated models using R Shiny. Additionally, clinical data from 12 patients with newly diagnosed osteosarcoma were collected and used as the validation set to preliminarily verify the predictive ability of the popPK model and the dose optimizer tool.
resultsBody surface area (BSA) was the most significant covariate for compartment distribution. Creatinine clearance (CrCL) and co-administration of NSAIDs were introduced as predictors for central compartmental and peripheral compartmental clearance, respectively. Co-administration of NSAIDs was associated with significantly higher MTX concentrations at 72 h (p = 0.019). The dose optimizer tool exhibited a high consistency in predicting MTX AUC compared to the actual AUC (r = 0.821, p < 0.001) in the validation set.
conclusionThe dose optimizer tool could be used to estimate individual PK parameters, and optimize personalized MTX therapy in particular patients.
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