Population Pharmacokinetics and Covariate Analysis of Methotrexate in Pediatric Acute Lymphoblastic Leukemia.

Purpose: The current study was designed to develop and validate a population pharmacokinetic (PPK) model of methotrexate (MTX) in pediatric patients with acute lymphoblastic leukemia (ALL). We aimed to develop a PPK model to evaluate the effects of potential covariates and explore dosing regimen.

Patients and methods: We retrospectively analyzed data from 214 pediatric patients with ALL who received high-dose methotrexate (HD-MTX) therapy, incorporating a total of 1672 plasma concentration measurements. Plasma samples were assayed using Enzyme-Multiplied Immunoassay Technique (EMIT). The PPK model was developed using a nonlinear mixed-effects model approach utilizing the NONMEM 7.4 software. Monte Carlo simulation was conducted to optimize the dosage regimen.

Results: A two-compartment model with a 1-year age cutoff was found to adequately describe the PK disposition of MTX. The population typical values for clearance (CL) and volume of distribution (V) were 4.46 L/h and 15.9 L, respectively. Estimated glomerular filtration rate (eGFR) was identified as the most significant covariate, with body weight and blood urea nitrogen (BUN) also emerging as primary factors influencing CL. The model exhibited satisfactory predictive performance, with bootstrap analysis showing a 93.6% success rate. For external validation, the median prediction error (MPE) and median absolute prediction error (MAPE) were -3.99% and 22.4%, respectively. Additionally, 46.36% of prediction errors fell within ±20%, and 64.55% within ±30%, confirming the model's acceptable predictive performance. Monte Carlo simulations showed that optimized loading doses significantly improved steady-state MTX levels and reduced delayed elimination, especially in patients with renal impairment (eGFR < 100 mL/min/1.73m²).

Conclusion: The PPK model established in this study can well predict the MTX exposure level in children with ALL, and it clearly identifies renal function status as a key basis for adjusting the loading dose. Combined with the results of Monte Carlo simulations, we propose that for patients with mild to moderate renal insufficiency, increasing the loading dose and prolonging the infusion time can improve the steady-state concentration compliance rate while reducing the risk of delayed excretion, providing a more targeted reference for clinical decision-making.