Population Pharmacokinetics of High-Dose Methotrexate After Intravenous Administration in Pediatric Patients With Osteosarcoma

Abstract

The goal of this study was to establish the population pharmacokinetics (PK) of high-dose methotrexate (HD-MTX) treatment in children with osteosarcoma and to explore the influence of patient covariates and between-occasion variability on drug disposition. Patient covariates and concentration-time data were collected. PK data analysis from 209 HD-MTX cycles from 14 patients was performed using the population approach (NONMEM V). Internal and external validations were performed to confirm the model. PK of methotrexate was best described by a 2-compartment open PK model with first-order elimination from the central compartment. Between-subject variability (BSV) was included in total plasma clearance (CL) and in central compartment distribution volume (V1) [coefficient of variation (CV) 11.9% and 8.9%, respectively]. The CV of BSV in the residual error was 25.5%. Between-occasion variability was only retained for CL (CV 8.2%). RE consisted of a proportional error of 41.6%. Age and body weight in CL and body weight in V1 were identified as the appropriate covariates. The final estimates of total CL and V1 were given by the equations CL = 88.5.(AGE/15) + 27.4 x (WGT/50) L/d and V1 = 11.0 + 5.6 x (WGT/50) L, respectively. Internal validation results showed that the 95% confidence interval covered all the observed MTX concentrations. Mean bias and precision of the individual predicted concentrations, calculated in a validation dataset, resulted in -1.36% and 19.71%, respectively. A population PK model was developed for HD-MTX in children with osteosarcoma. Validation studies confirmed the suitability of the model for further dose individualization by means of a Bayesian approach.

Developing Population Pharmacokinetic Parameters for High-Dose Methotrexate Therapy: Implication of Correlations among Developed Parameters for Individual Parameter Estimation Using the Bayesian Least-Squares Method

“…Cases in which MTX concentrations were determined at 5 or more time points were chosen to develop population parameters. The points of determinations were fixed as follows: 3,6,12,24,48,72,96,120,144, and 192 h after the initiation of infusion. The first point of determination was omitted in some cases treated with regimen B, and the end point was decided for each case by physicians.…”

“…With the exception of the combination of the parameters with a relationship equation, 21 combinations were available. To select combinations with the weakest correlations among the parameters, combinations with 0.5 or above absolute values of the correlation coefficients among the parameters shown in Tables 2 and 3 were excluded. Two combinations were identified: "V 1 , k 10 , k 12 , and k 21 " and "V 1 , Q, k 12 , and k 21 ." The sum of the absolute value of correlation coefficients among the parameters selected in these 2 combinations were similar in Table 2 (1.82, 1.62, respectively), but were markedly different in Table 3 (1.05, 2.22, respectively).…”

“…The sum of the absolute value of correlation coefficients among the parameters selected in these 2 combinations were similar in Table 2 (1.82, 1.62, respectively), but were markedly different in Table 3 (1.05, 2.22, respectively). Therefore, we selected V 1 , k 10 , k 12 , and k 21 as the combination of population parameters for regimens A and B, and the mean and coefficient of variation (CV, used as the interindividual variation) of these parameters are shown in Table 4.…”

“…In addition, because an increase in the parameters included in the pharmacokinetic models increases the possible correlations among the parameters, this issue should be considered especially for medications in which the pharmacokinetic pro-file is a 2 or higher dimensional compartment model. MTX pharmacokinetics were previously shown to be accounted for by a 2-compartment model, [9][10][11][12][13][14][15][16][17][18][19] which suggests that this issue needs to be considered. However, to the best of our knowledge, correlations and/or covariance among population parameters have not been considered especially in the clinical use of Bayesian estimation performed using the Bayesian least-squares method.…”

“…Several population parameters have already been developed for cases receiving HD-MTX, and the usefulness of these parameters has been tested. [9][10][11][12][13][14][15][16][17][18][19] Many of these studies were performed using NONMEM, which has been used as the standard method for population pharmacokinetic analyses including Bayesian estimation. However, this software is rarely used in clinical settings because of the difficulties associated with its use.…”