Population pharmacokinetic study of methotrexate in patients with lymphoid malignancy

Understanding hemoglobin contribution to high-dose methotrexate disposition-population pharmacokinetics in pediatric patients with hematological malignancies

PURPOSE

The aim of the present study was to develop a population pharmacokinetic model for methotrexate (MTX) during high-dose treatment (HDMTX) in pediatric patients with acute lymphoblastic leukemia (ALL) and non-Hodgkin's lymphoma (NHL) and to describe the influence of variability factors.

METHODS

The study included 50 patients of both sexes (aged 1-18 years) who received 3 or 5 g/m2 of HDMTX. A nonlinear mixed effect modeling approach was applied for data analysis. Parameter estimation was performed by first-order conditional estimation method with interaction (FOCEI), whereas stepwise covariate modeling was used to assess variability factors.

RESULTS

The final model is a two-compartment model that incorporates the effect of body surface area and the influence of hemoglobin and serum creatinine on MTX clearance (CL). Population pharmacokinetic values for a typical subject were estimated at 5.75 L/h/m2 for clearance (CL), 21.3 L/m2 for volume of the central compartment (V1), 8.2 L/m2 for volume of the peripheral compartment (V2), and 0.087 L/h/m2 for intercompartmental clearance (Q). According to the final model, MTX CL decreases with increasing serum creatinine, whereas a positive effect was captured for hemoglobin. A difference of almost 32% in MTX CL was observed among patients' hemoglobin values reported in the study.

CONCLUSION

The developed population pharmacokinetic model can contribute to the therapy optimization during HDMTX in pediatric patients with ALL and NHL. In addition to renal function and body weight, it describes the influence of hemoglobin on CL, allowing better understanding of its contribution to the disposition of HDMTX.

External Evaluation of Population Pharmacokinetic Models for High-Dose Methotrexate in Adult Patients with Hematological Tumors

Currently, numerous population pharmacokinetic (popPK) models for methotrexate (MTX) have been published for estimating PK parameters and variability. However, it is unclear whether the accuracy of these models is sufficient for clinical application. The aim of this study is to evaluate published models and assess their predictive performance according to the standards of scientific research. A total of 237 samples from 74 adult patients who underwent high-dose MTX (HDMTX) treatment at Shanghai Changzheng Hospital were collected. The software package NONMEM was used to perform an external evaluation for each model, including prediction-based diagnosis, simulation-based diagnosis, and Bayesian forecasting. The simulation-based diagnosis includes normalized prediction distribution error (NPDE) and visual predictive check (VPC). Following screening, 7 candidate models suitable for external validation were identified for comparison. However, none of these models exhibited excellent predictive performance. Bayesian simulation results indicated that the prediction precision and accuracy of all models significantly improved when incorporating prior concentration information. The published popPK models for MTX exhibit significant differences in their predictive performance, and none of the models were able to accurately predict MTX concentrations in our data set. Therefore, before adopting any model in clinical practice, extensive evaluation should be conducted.

Factors influencing methotrexate pharmacokinetics highlight the need for individualized dose adjustment: a systematic review

PURPOSE

To develop a population pharmacokinetic (PPK) model for methotrexate (MTX) dosage for all ages, assess the association between concentration and clearance, and determine covariates affecting MTX disposition.

METHODS

We compared MTX PK profiles among neonates, children, and adults by performing a systematic literature search for published population MTX models and conducted a Monte Carlo-based meta-analysis. Subsequently, we evaluated study quality and covariates significantly affecting dosage regimens and compared LDMTX and HDMTX PK profiles.

RESULTS

Of the total 40 studies included, 34 were HDMTX, and six were LDMTX studies. For HDMTX, three studies involving neonates reported estimated apparent clearances (median, range) of 0.53 (0.27-0.77) L/kg/h; for 14 studies involving children, 0.23 (0.07-0.23) L/kg/h; and for 13 involving adults, 0.11 (0.03-0.22) L/kg/h. Neonates had a higher volume of distribution than children and adults. For LDMTX studies, apparent clearance was 0.085 (0.05-1.68) L/kg/h, and volume of distribution was 0.25 (0.018-0.47) L/kg, lower than those of HDMTX studies, with large between-subject variability. Bodyweight significantly influenced apparent clearance and volume of distribution, whereas renal function mainly influenced clearance. Mutations in certain genes reduced MTX clearance by 8-35.3%, whereas those in others increased it by 15-48%. Body surface area (BSA) significantly influenced apparent clearance with a median reduction of 51% when BSA increased in pediatric patients.

CONCLUSIONS

Methotrexate dosage regimens were primarily based on body surface area and renal function. Further studies are needed to evaluate MTX pharmacokinetics and pharmacodynamics in both children (especially infants) and adults.

A new pharmacokinetic model of urinary methotrexate to assess adherence in rheumatoid arthritis

BACKGROUND AND OBJECTIVES

Methotrexate (MTX) is the first-line therapy for rheumatoid arthritis (RA). While therapeutic adherence is essential to successful management, no objective MTX assay is currently available. Using population pharmacokinetic modelling (PopPK), our objective was to describe the urinary MTX (MTXu) kinetics in treated patients and to evaluate its abilities to assess the MTX-adherence.

METHODS

The association between urinary methotrexate level and methotrexate administration was assessed using a generalized linear model. Then, a population pharmacokinetic model was developed based on data from 59 patients using with Monolix 2021. R2. Simulations were run to establish a reference kinetic profile and evaluate the proportion of samples predicted as true positives.

RESULTS

Compared to the control group, multivariate analysis showed that MTXu was independently associated with methotrexate administration (p < 0.0001) with a sensitivity and specificity greater than 99%. The final PopPK model selected was a two-compartment model with first-order absorption and elimination. Internal and external validation of the model met all predefined criteria. When using an analytical assay with a LOQ equal to 1 nM, the proportion of samples predicted as true positives is over 90%, as a function of MTX dose (7.5-25 mg/week) and post-administration sampling days (1-7 days).

CONCLUSION

We developed a pharmacokinetic model able to describe expected patterns of urinary methotrexate. This allowed us to propose a new objective test of MTX adherence, which could help in routine practice to differentiate patients who are truly unresponsive to methotrexate from those who are unresponsive because of non-adherence.

External evaluation and systematic review of population pharmacokinetic models for high-dose methotrexate in cancer patients

Several population pharmacokinetic (PPK) models have been established to optimize the therapeutic regimen and reduce the toxicity of high-dose methotrexate (HDMTX) in patients with cancer. However, their predictive performance when extrapolated to different clinical centers was unknown. In this study, we aimed to externally evaluate the predictive ability of HDMTX PPK models and determine the potential influencing factors. We searched the literature and determined the predictive performance of the selected models using methotrexate concentrations in 721 samples from 60 patients in the First Affiliated Hospital of the Navy Medical University. Prediction-based diagnostics and simulation-based normalized prediction distribution errors (NPDE) were used to evaluate the predictive performance of the models. The influence of prior information was also assessed using Bayesian forecasting, and the potential factors affecting model predictability were investigated. Thirty models extracted from published PPK studies were assessed. Prediction-based diagnostics showed that the number of compartments potentially influenced model transferability, and simulation-based NPDE indicated model misspecification. Bayesian forecasting significantly improved the predictive performance of the models. Various factors, including bioassays, covariates, and population diagnosis, influence model extrapolation. The published models were unsatisfactory for all prediction-based diagnostics, except for the 24 h methotrexate concentration monitoring and simulation-based diagnostics, making them inappropriate for direct extrapolation. Moreover, Bayesian forecasting combined therapeutic drug monitoring could improve the predictive performance of the models.

Population pharmacokinetics of methotrexate in pediatric patients with acute lymphoblastic leukemia and malignant lymphoma

1. This study aimed to identify physiological and pharmacogenomic covariates and develop a population pharmacokinetic model of high-dose methotrexate (HD-MTX) in Chinese pediatric patients with acute lymphoblastic leukemia (ALL) and malignant lymphoma.2. A total 731 MTX courses and 1658 MTX plasm concentration from 205 pediatric patients with ALL and malignant lymphoma were analyzing using a nonlinear mixed-effects model technique. 47 SNPs in 16 MTX-related gene were genotyped and screened as covariates. A PPK model was established to determine the influence of covariates such as body surface area (BSA), age, laboratory test value, and SNPs on the pharmacokinetic process of HD-MTX.3. Two-compartmental model with allometric scaling using BSA could nicely characterize the in vivo behavior of HD-MTX. After accounting for body size, rs17004785 and rs4148416 were the covariates that influence MTX clearance (CL). The PPK model obtained was: CL =9.33 * (BSA/1.73) ^0.75 * e^{0.13*rs17004785} * e^{0.39*rs4148416} * e^ηCL, Vc =24.98 * (BSA/1.73) * e^ηvc, Q = 0.18 * (BSA/1.73) ^0.75 * e^ηQ and Vp =4.70 * (BSA/1.73) * e^ηvp.4. The established model combined with Bayesian approach could estimate individual pharmacokinetic parameters and optimize personalized HD-MTX therapy for pediatric patients with ALL and malignant lymphoma.

Evaluation and Application of Population Pharmacokinetic Models for Identifying Delayed Methotrexate Elimination in Patients With Primary Central Nervous System Lymphoma

Objective: Several population pharmacokinetic (popPK) models have been developed to determine the sources of methotrexate (MTX) PK variability. It remains unknown if these published models are precise enough for use or if a new model needs to be built. The aims of this study were to 1) assess the predictability of published models and 2) analyze the potential risk factors for delayed MTX elimination.

Methods: A total of 1458 MTX plasma concentrations, including 377 courses (1–17 per patient), were collected from 77 patients who were receiving high-dose MTX for the treatment of primary central nervous system lymphoma in Huashan Hospital. PopPK analysis was performed using the NONMEM® software package. Previously published popPK models were selected and rebuilt. A new popPK model was then constructed to screen potential covariates using a stepwise approach. The covariates were included based on the combination of theoretical mechanisms and data properties. Goodness-of-fit plots, bootstrap, and prediction- and simulation-based diagnostics were used to determine the stability and predictive performance of both the published and newly built models. Monte Carlo simulations were conducted to qualify the influence of risk factors on the incidence of delayed elimination.

Results: Among the eight evaluated published models, none presented acceptable values of bias or inaccuracy. A two-compartment model was employed in the newly built model to describe the PK of MTX. The estimated mean clearance (CL/F) was 4.91 L h⁻¹ (relative standard error: 3.7%). Creatinine clearance, albumin, and age were identified as covariates of MTX CL/F. The median and median absolute prediction errors of the final model were -10.2 and 36.4%, respectively. Results of goodness-of-fit plots, bootstrap, and prediction-corrected visual predictive checks indicated the high predictability of the final model.

Conclusions: Current published models are not sufficiently reliable for cross-center use. The elderly patients and those with renal dysfunction, hypoalbuminemia are at higher risk of delayed elimination.

A Systematic Review of Population Pharmacokinetic Models of Methotrexate

BACKGROUND AND OBJECTIVES

Methotrexate (MTX) is widely used for the treatment of a variety of neoplastic and autoimmune diseases. However, its toxicity and efficacy varied greatly among individuals, and they could be predicted by its pharmacokinetics. Many population pharmacokinetic models have been published to describe MTX pharmacokinetics. The objective of this systematic review was to summarize and discuss covariates with significant influence on MTX pharmacokinetics.

METHODS

We searched PubMed and EMBASE databases from their inception to April 2021 for population pharmacokinetic of MTX. The articles were screened by inclusion and exclusion criteria. The characteristics of studies and information for model construction and validation were extracted, summarized and discussed.

RESULTS

Thirty-five articles were included. The two-compartment model well described the pharmacokinetic behavior of MTX. For inter-individual variability, an exponential distribution error model was usually used for high-dose MTX population pharmacokinetic models, while a proportional distribution error model was used for low-dose MTX population pharmacokinetic models. Proportional and combined proportional and additive error models were used to describe residual error. Renal function was an independent indicator of MTX clearance. Body weight, age, gene polymorphisms (SLCO1B1, ABCC2, ABCB1, ABCG2 and MTHFR) and co-medications (proton pump inhibitors, non-steroidal anti-inflammatory drug, dexamethasone, vancomycin, penicillin and salicylic acid) could influence MTX clearance. Body weight, body surface area, age and dosage regimen have significant influence on MTX central compartment volume. Internal bootstrap test, external validation and visual predictive check were used to evaluate model predictive ability.

CONCLUSIONS

Various covariates could affect MTX pharmacokinetics, and their relationships have been summarized and discussed. This review will be helpful for researchers to develop their own population pharmacokinetic models and select appropriate models for individualized therapy of MTX.

Easy and reliable maximum a posteriori Bayesian estimation of pharmacokinetic parameters with the open-source R package mapbayr

Pharmacokinetic (PK) parameter estimation is a critical and complex step in the model‐informed precision dosing (MIPD) approach. The mapbayr package was developed to perform maximum a posteriori Bayesian estimation (MAP‐BE) in R from any population PK model coded in mrgsolve. The performances of mapbayr were assessed using two approaches. First, “test” models with different features were coded, for example, first‐order and zero‐order absorption, lag time, time‐varying covariates, Michaelis–Menten elimination, combined and exponential residual error, parent drug and metabolite, and small or large inter‐individual variability (IIV). A total of 4000 PK profiles (combining single/multiple dosing and rich/sparse sampling) were simulated from each test model, and MAP‐BE of parameters was performed in both mapbayr and NONMEM. Second, a similar procedure was conducted with seven “real” previously published models to compare mapbayr and NONMEM on a PK outcome used in MIPD. For the test models, 98% of mapbayr estimations were identical to those given by NONMEM. Some discordances could be observed when dose‐related parameters were estimated or when models with large IIV were used. The exploration of objective function values suggested that mapbayr might outdo NONMEM in specific cases. For the real models, a concordance close to 100% on PK outcomes was observed. The mapbayr package provides a reliable solution to perform MAP‐BE of PK parameters in R. It also includes functions dedicated to data formatting and reporting and enables the creation of standalone Shiny web applications dedicated to MIPD, whatever the model or the clinical protocol and without additional software other than R.

Population Pharmacokinetics of High-Dose Methotrexate in Chinese Pediatric Patients With Acute Lymphoblastic Leukemia

High-dose methotrexate (HD-MTX) is widely used in pediatric acute lymphoblastic leukemia (ALL) treatment regimens. In this study, we aimed to develop a population pharmacokinetic (PK) model of HD-MTX in Chinese pediatric patients with ALL for designing personalized dosage regimens. In total, 4,517 MTX serum concentration data for 311 pediatric patients with ALL, aged 0.75–15.2 years and under HD-MTX treatment, were retrospectively collected at a tertiary Children’s Hospital in China. The non-linear mixed-effect model was used to establish the population PK model, using NONMEM software. The potential covariate effects of age, body weight, and biochemical measurements (renal and liver function) on MTX PK disposition were investigated. The model was then evaluated using goodness-of-fit, visual predictive check. MTX PK disposition was described using a three-compartment model reasonable well. Body weight, implemented as a fixed allometric function on all clearance and volume of distribution parameters, showed a substantial improvement in model fit. The final population model demonstrated that the MTX clearance estimate in a typical child with body weight of 19 kg was 6.9 L/h and the central distribution of volume estimate was 20.7 L. The serum creatinine significantly affected the MTX clearance, with a 0.97% decrease in clearance per 1 μmol/L of serum creatinine. Other covariates (e.g., age, sex, bilirubin, albumin, aspartate transaminase, concomitant medication) did not significantly affect PK properties of MTX. The proposed population PK model could describe the MTX concentration data in Chinese pediatric patients with ALL. This population PK model combined with a maximum a posteriori Bayesian approach could be used to estimate individual PK parameters, and optimize personalized MTX therapy in target patients, thus aiming to reduce toxicity and improve treatment outcomes.

Evaluation of body-surface-area adjusted dosing of high-dose methotrexate by population pharmacokinetics in a large cohort of cancer patients

Background

The aim of this study was to identify sources of variability including patient gender and body surface area (BSA) in pharmacokinetic (PK) exposure for high-dose methotrexate (MTX) continuous infusion in a large cohort of patients with hematological and solid malignancies.

Methods

We conducted a retrospective PK analysis of MTX plasma concentration data from hematological/oncological patients treated at the University Hospital of Cologne between 2005 and 2018. Nonlinear mixed effects modeling was performed. Covariate data on patient demographics and clinical chemistry parameters was incorporated to assess relationships with PK parameters. Simulations were conducted to compare exposure and probability of target attainment (PTA) under BSA adjusted, flat and stratified dosing regimens.

Results

Plasma concentration over time data (2182 measurements) from therapeutic drug monitoring from 229 patients was available. PK of MTX were best described by a three-compartment model. Values for clearance (CL) of 4.33 [2.95–5.92] L h^− 1 and central volume of distribution of 4.29 [1.81–7.33] L were estimated. An inter-occasion variability of 23.1% (coefficient of variation) and an inter-individual variability of 29.7% were associated to CL, which was 16 [7–25] % lower in women. Serum creatinine, patient age, sex and BSA were significantly related to CL of MTX. Simulations suggested that differences in PTA between flat and BSA-based dosing were marginal, with stratified dosing performing best overall.

Conclusion

A dosing scheme with doses stratified across BSA quartiles is suggested to optimize target exposure attainment. Influence of patient sex on CL of MTX is present but small in magnitude.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08443-x.

Body Surface Area Dosing of High-Dose Methotrexate Should Be Reconsidered, Particularly in Overweight, Adult Patients

BACKGROUND

High-dose methotrexate is used for treating several types of cancer. However, it is associated with a high risk of acute kidney injury (AKI), especially in patients with high MTX concentrations. Although therapeutic drug monitoring is performed to monitor MTX concentrations, it is unclear what concentration should be considered critical, thus requiring rescue protocols to prevent nephrotoxicity.

METHODS

Patients treated with high-dose methotrexate for lymphoma or acute lymphoblastic leukemia and those benefited from therapeutic drug monitoring were included. The relationship between MTX concentrations and the presence or absence of AKI was assessed. MTX concentrations were analyzed using a population pharmacokinetic approach. Specific attention was given to morphological covariates because MTX doses are individualized according to body surface area (BSA).

RESULTS

In total, 328 patients and 657 cycles of treatment were analyzed. Higher MTX concentrations were observed in the AKI+ group. For cycle 1, all patients showing an MTX concentration >6 µM at 36 hours or >2 µM at 48 hours after infusion developed nephrotoxicity. The final pharmacokinetic model had 2 compartments and included the effect of age on clearance (CL) and of body weight on peripheral distribution volume. None of the morphological covariates tested on CL led to significant improvement in the model. Higher MTX concentrations were observed in patients with extreme BSA values (≥2 m2) or body mass index (≥25 kg/m2). Patients with AKI who received at least 1 cycle had higher BSA and BMI.

CONCLUSIONS

The results from this study provide additional information on the relationship between MTX concentration and nephrotoxicity. Patients with a plasma MTX concentration >6 µM at 36 hours were more likely to manifest AKI. In addition, the results suggest that overweight patients have a high AKI risk and that BSA-based adjustment of MTX dose is not appropriate.

Pharmacokinetics and pharmacogenetics of high-dose methotrexate in Chinese adult patients with non-Hodgkin lymphoma: a population analysis

PURPOSE

High-dose methotrexate (HD-MTX) is widely used in the treatment of non-Hodgkin lymphoma (NHL), but the pharmacokinetic properties of HD-MTX in Chinese adult patients with NHL have not yet been established through an approach that integrates genetic covariates. The purposes of this study were to identify both physiological and pharmacogenomic covariates that can explain the inter- and intraindividual pharmacokinetic variability of MTX in Chinese adult patients with NHL and to explore a new sampling strategy for predicting delayed MTX elimination.

METHODS

A total of 852 MTX concentrations from 91 adult patients with NHL were analyzed using the nonlinear mixed-effects modeling method. FPGS, GGH, SLCO1B1, ABCB1 and MTHFR were genotyped using the Sequenom MassARRAY technology platform and were screened as covariates. The ability of different sampling strategies to predict the MTX concentration at 72 h was assessed through maximum a posteriori Bayesian forecasting using a validation dataset (18 patients).

RESULTS

A two-compartment model adequately described the data, and the estimated mean MTX clearance (CL) was 6.03 L/h (9%). Creatinine clearance (CrCL) was identified as a covariate for CL, whereas the intercompartmental clearance (Q) was significantly affected by the body surface area (BSA). However, none of the genotypes exerted a significant effect on the pharmacokinetic properties of MTX. The percentage of patients with concentrations below 0.2 µmol/L at 72 h decreased from 65.6 to 42.6% when the CrCL decreased from 90 to 60 ml/min/1.73 m² with a scheduled dosing of 3 g/m², and the same trend was observed with dose regimens of 1 g/m² and 2 g/m². Bayesian forecasting using the MTX concentrations at 24 and 42 h provided the best predictive performance for estimating the MTX concentration at 72 h after dosing.

CONCLUSIONS

The MTX population pharmacokinetic model developed in this study might provide useful information for establishing personalized therapy involving MTX for the treatment of adult patients with NHL.

Population pharmacokinetics of high-dose methotrexate in Chinese pediatric patients with medulloblastoma

Methotrexate (MTX) pharmacokinetics has substantial inter-individual variability and toxicity. In children with medulloblastoma treated with high-dose methotrexate (HD-MTX), the pharmacokinetic properties of methotrexate have not been established. A total of 660 serum samples from 105 pediatric patients with medulloblastoma were included in a population pharmacokinetic (PPK) analysis of methotrexate by using the nonlinear mixed-effects modeling method. The basic one-compartment population pharmacokinetic model was established by NONMEM software and the first-order conditional estimation (FOCE) method, and the final covariate model was obtained by the stepwise regression method. Weight (WT), creatinine clearance (CrCL), and whether the treatment was combined with dexamethasone (DEX) were covariates that had significant effects on the clearance rate (CL) of the model. The pharmacokinetic equation of CL in the final covariate model was as follows: CL_i = 9.23× (1 + 0.0005× (θ_CrCL -105.78)) × (1 + 0.0017× (θ_WT -16)) × e^ηcl,i (L/h), IF (θ_DEX ) CL_i = 1.19× CL_i (L/h). The estimation accuracy of all pharmacokinetic parameters were acceptable (relative standard error < 14.74%). The goodness-of-fit diagram and bootstrap tests indicated that the final PPK model was stable with acceptable predictive ability. The PPK model may be useful for determining personalized medication levels in pediatric medulloblastoma patients undergoing HD-MTX therapy.

The Population Pharmacokinetics of High-Dose Methotrexate in Infants with Acute Lymphoblastic Leukemia Highlight the Need for Bedside Individualized Dose Adjustment: A Report from the Children's Oncology Group

BACKGROUND

Infants with acute lymphoblastic leukemia (ALL) treated with high-dose methotrexate may have reduced methotrexate clearance (CL) due to renal immaturity, which may predispose them to toxicity.

OBJECTIVE

The aim of this study was to develop a population pharmacokinetic (PK) model of methotrexate in infants with ALL.

METHODS

A total of 672 methotrexate plasma concentrations were obtained from 71 infants enrolled in the Children's Oncology Group (COG) Clinical Trial P9407. Infants received methotrexate 4 g/m2 intravenously for four cycles during weeks 4-12 of intensification. A population PK analysis was performed using NONMEM® version 7.4. The final model was evaluated using a non-parametric bootstrap and a visual predictive check. Simulations were performed to evaluate methotrexate dose and the utility of a bedside algorithm for dose individualization.

RESULTS

Methotrexate was best characterized by a two-compartment model with allometric scaling. Weight was the only covariate included in the final model. The coefficient of variation for interoccasion variability (IOV) on CL was relatively high at 25.4%, compared with the interindividual variability for CL and central volume of distribution (10.7% and 13.2%, respectively). Simulations identified that 21.1% of simulated infants benefitted from bedside dose adjustment, and adjustment of methotrexate doses during infusions can avoid supratherapeutic concentrations.

CONCLUSION

Infants treated with high-dose methotrexate demonstrated a relatively high degree of IOV in methotrexate CL. The magnitude of IOV in the CL of methotrexate suggests that use of a bedside algorithm may avoid supratherapeutic methotrexate concentrations resulting from high IOV in methotrexate CL.

Population Pharmacokinetic Study and Individual Dose Adjustments of High-Dose Methotrexate in Chinese Pediatric Patients With Acute Lymphoblastic Leukemia or Osteosarcoma

High-dose methotrexate (>0.5 g/m² ) is among the first-line chemotherapeutic agents used in treating acute lymphoblastic leukemia (ALL) and osteosarcoma in children. Despite rapid hydration, leucovorin rescue, and routine therapeutic drug monitoring, severe toxicity is not uncommon. This study aimed at developing population pharmacokinetic (popPK) models of high-dose methotrexate for ALL and osteosarcoma and demonstrating the possibility and convenience of popPK model-based individual dose optimization using R and shiny, which is more accessible, efficient, and clinician-friendly than NONMEM. The final data set consists of 36 ALL (354 observations) and 16 osteosarcoma (585 observations) patients. Covariate model building and parameter estimations were done using NONMEM and Perl-speaks-NONMEM. Diagnostic Plots and bootstrapping validated the models' performance and stability. The dose optimizer developed based on the validated models can obtain identical individual parameter estimates as NONMEM. Compared to calling a NONMEM execution and reading its output, estimating individual parameters within R reduces the execution time from 8.7-12.8 seconds to 0.4-1.0 second. For each subject, the dose optimizer can recommend (1) an individualized optimal dose and (2) an individualized range of doses. For osteosarcoma, recommended optimal doses by the optimizer resemble the final doses at which the subjects were eventually stabilized. The dose optimizers developed demonstrated the potential to inform dose adjustments using a model-based, convenient, and efficient tool for high-dose methotrexate. Although the dose optimizer is not meant to replace clinical judgment, it provides the clinician with the individual pharmacokinetics perspective by recommending the (range of) optimal dose.

Population Pharmacokinetics of High-Dose Methotrexate in Patients With Primary Central Nervous System Lymphoma

The intra- and inter-individual variances of methotrexate (MTX) pharmacokinetics are extremely large, and the pharmacokinetic property of MTX in patients with primary central nervous system lymphoma (PCNSL) is unestablished. A total of 701 MTX plasma concentrations from 98 patients with PCNSL under high-dose MTX therapy were used to develop the population pharmacokinetic (popPK) model of MTX by using the nonlinear mixed-effects modeling method. A 2-compartment model was employed to describe the pharmacokinetic property of MTX. In the final popPK model, inclusion of serum creatinine and body surface area significantly reduced objective function value for clearance over the base model (p <0.001), and inclusion of age significantly reduced objective function value for distribution volume of central compartment (V_c) over the base model (p <0.001). In the final popPK model, the inter-individual clearance = 6.67 × (SCR/68.1)^-0.48 × (BSA/1.75)^1.17; V_c = 24.46 × (age/57.16)^0.81. The precision of all parameters was acceptable (relative standard error <28.61%). Bootstrap and visual predictive check results indicated that the final popPK model was stable with acceptable predictive ability. The popPK model may be useful for personalized medication in PCNSL patients under high-dose MTX therapy. Further studies are warranted to confirm the results.

Delayed methotrexate excretion in infants and young children with primary central nervous system tumors and postoperative fluid collections

PURPOSE

High-dose methotrexate (HD-MTX) has been used to treat children with central nervous system tumors. Accumulation of MTX within pleural, peritoneal, or cardiac effusions has led to delayed excretion and increased risk of systemic toxicity. This retrospective study analyzed the association of intracranial post-resection fluid collections with MTX plasma disposition in infants and young children with brain tumors.

METHODS

Brain MRI findings were analyzed for postoperative intracranial fluid collections in 75 pediatric patients treated with HD-MTX and for whom serial MTX plasma concentrations (MTX) were collected. Delayed plasma excretion was defined as (MTX) ≥1 μM at 42 hours (h). Leucovorin was administered at 42 h and then every 6 h until (MTX) <0.1 μM. Population and individual MTX pharmacokinetic parameters were estimated by nonlinear mixed-effects modeling.

RESULTS

Fifty-eight patients had intracranial fluid collections present. Population average (inter-individual variation) MTX clearance was 96.0 ml/min/m² (41.1 CV %) and increased with age. Of the patients with intracranial fluid collections, 24 had delayed excretion; only 2 of the 17 without fluid collections (P < 0.04) had delayed excretion. Eleven patients had grade 3 or 4 toxicities attributed to HD-MTX. No significant difference was observed in intracranial fluid collection, total leucovorin dosing, or hydration fluids between those with and without toxicity.

CONCLUSIONS

Although an intracranial fluid collection is associated with delayed MTX excretion, HD-MTX can be safely administered with monitoring of infants and young children with intracranial fluid collections. Infants younger than 1 year may need additional monitoring to avoid toxicity.

Urinary coproporphyrin I/(I + III) ratio as a surrogate for MRP2 or other transporter activities involved in methotrexate clearance

AIMS

The urinary coproporphyrin I/(I + III) ratio may be a surrogate for MRP2 activity. We conducted a prospective study in patients receiving methotrexate (MTX) to examine the relationship between this ratio and the pharmacokinetics of a MRP2 substrate.

METHODS

Three urine samples were collected from 81 patients for UCP I/(I + III) ratio determination: one before (P1), one at the end of MTX infusion (P2), and one on the day of hospital discharge (P3). Three polymorphisms of ABCC2 were analysed and their relationships with basal UCP I/(I + III) ratio values assessed. All associated drugs were recorded and a drug interaction score (DIS) was assigned. Population pharmacokinetic analysis was conducted to assess whether MTX clearance (MTXCL) was associated with the basal UCP I/(I + III) ratio, its variation during MTX infusion, the DIS or other common covariates.

RESULTS

The basal UCP I/(I + III) ratio was not associated with ABCC2 polymorphisms and did not differ according to the DIS. Significant changes in the ratio were observed over time, with an increase between P1 and P2 and a decrease at P3 (P < 0.001). No association was found between basal UCP I/(I + III) ratio and MTXCL. The final model indicates that MTXCL was dependent on the change in the ratio between P1 and P3, DIS and creatinine clearance.

CONCLUSION

The basal UCP I/(I + III) ratio is not predictive of MTXCL. However, it is sensitive to the presence of MTX, so it is plausible that it reflects a function modified in response to the drug.

Methotrexate and 5-aminoimidazole-4-carboxamide riboside exert synergistic anticancer action against human breast cancer and hepatocellular carcinoma

AIM

To investigate the influences of methotrexate (MTX) on the anticancer actions and pharmacokinetics of 5-aminoimidazole-4-carboxamide riboside (AICA riboside) in human breast cancer and hepatocellular carcinoma.

METHODS

Human breast cancer cell line MCF-7 and human hepatocellular carcinoma cell line HepG2 were examined. The cell proliferation was assessed using a sulforhodamine B assay. Western blotting and radioactivity assays were used to analyze the phosphorylation of AMPK. The DNA synthesis was analyzed with BrdU incorporation. Nude mice bearing MCF-7 cell xenografts were used to for in vivo study. MTX (50 mg/kg, ip, per week) and AICA riboside (200 mg/kg, ip, every other day) were administered the animals for 2 weeks. The concentrations of AICA riboside and its active metabolite AICA ribotide in the plasma and tumors were measured with HPLC.

RESULTS

Synergistic cytotoxicity in vitro was observed with MTX (0.1, 0.5, and 1 μmol/L) combined with AICA riboside (0.25-1 mmol/L) in MCF-7 cells, and with MTX (0.5 and 1 μmol/L) combined with AICA riboside (0.5 and 1 mmol/L) in HepG2 cells. MTX (1 μmol/L) significantly enhanced the AICA riboside-induced AMPK activation and BrdU incorporation in both MCF-7 and HepG2 cells. Co-treatment with MTX and AICA riboside exerted more potent inhibition on the tumor growth in nude mice than either drug alone. After injection of AICA riboside (200 mg/kg, iv) in nude mice bearing MCF-7 xenografts, MTX (50 mg/kg, iv) significantly increased the concentrations of AICA riboside and its active metabolite AICA ribotide in tumors.

CONCLUSION

MTX and AICA riboside exert synergistic anticancer action against MCF-7 and HepG2 cells in vitro and in vivo. MTX increases the concentration of AICA riboside and its active metabolite AICA ribotide in tumors in vivo.

Between-course targeting of methotrexate exposure using pharmacokinetically guided dosage adjustments

PURPOSE

It is advantageous to individualize high-dose methotrexate (HDMTX) to maintain adequate exposure while minimizing toxicities. Previously, we accomplished this through within-course dose adjustments.

METHODS

In this study, we evaluated a strategy to individualize HDMTX based on clearance of each individual's previous course of HDMTX in 485 patients with newly diagnosed acute lymphoblastic leukemia. Doses were individualized to achieve a steady-state plasma concentration (Cpss) of 33 or 65 μM (approximately 2.5 or 5 g/m(2)/day) for low- and standard-/high-risk patients, respectively.

RESULTS

Individualized doses resulted in 70 and 63 % of courses being within 20 % of the targeted Cpss in the low- and standard-/high-risk arms, respectively, compared to 60 % (p < 0.001) and 61 % (p = 0.43) with conventionally dosed therapy. Only 1.3 % of the individualized courses in the standard-/high-risk arm had a Cpss greater than 50 % above the target compared to 7.3 % (p < 0.001) in conventionally dosed therapy. We observed a low rate (8.5 % of courses) of grade 3-4 toxicities. The odds of gastrointestinal toxicity were related to methotrexate plasma concentrations in both the low (p = 0.021)- and standard-/high-risk groups (p = 0.003).

CONCLUSIONS

Individualizing HDMTX based on the clearance from the prior course resulted in fewer extreme Cpss values and less delayed excretion compared to conventional dosing.

Population PK/PD model of homocysteine concentrations after high-dose methotrexate treatment in patients with acute lymphoblastic leukemia

Elevated homocysteine concentrations have been associated with methotrexate-induced neurotoxicity. Based on methotrexate and homocysteine plasma concentrations of 494 children with acute lymphoblastic leukemia treated with high-dose methotrexate in the TOTAL XV study, a pharmacokinetic/pharmacodynamic (PK/PD) model was built with NONMEM. Several compartment and indirect response models were investigated. The pharmacokinetic disposition of methotrexate was best described by a two-compartment model. Homocysteine concentrations were included by an indirect response model where methotrexate inhibition of the homocysteine elimination rate was described by an E_max model. The homocysteine baseline level was found to be age-dependent. Simulations revealed that folinate rescue therapy does not affect peak concentrations of homocysteine but leads to a modestly reduced homocysteine exposure. In conclusion, our PK/PD model describes the increase of methotrexate-induced HCY concentrations with satisfactory precision and can be applied to assess the effect of folinate regimens on the HCY concentration-time course.

The prognostic value of serum methotrexate area under curve in elderly primary CNS lymphoma patients

Studies on pharmacokinetics and pharmacodynamics of high-dose methotrexate chemotherapy (HD-MTX) in elderly primary central nervous system lymphoma (PCNSL) patients are rare. MTX exposure time has recently been proposed as an outcome determining factor in PCNSL. We investigated 49 immunocompetent PCNSL patients (female N=30, male N=19, median age 73 years) who were treated according to HD-MTX-based protocols. A two-compartment pharmacokinetic model was used to describe the MTX clearance. Response to treatment was assessed by MRI. We used multivariable models to investigate the association between MTX exposure and tumor response as well as survival. Dose normalized MTX peak serum levels [C (max), μmol/L g] and dose normalized area under the curve [AUC(dn), μmol h/L g] were higher in females than in males, respectively [59.4 (f) vs. 48.1 (m), P<0.001; 373.2 (f) vs. 271.9 (m), P=0.008]. Increasing AUC was inversely correlated with tumor response. AUC values above 2,126 h μmol/L were independently associated with shorter overall and progression-free survival [hazard ratio (HR), 4.56, 95 % CI 1.74-11.94; HR 2.87, 95 % CI 1.18-7.00]. Exceedingly high MTX AUC levels can have a negative impact on progression-free and overall survivals in elderly PCNSL patients.

Optimal sampling strategy development methodology using maximum a posteriori Bayesian estimation

Maximum a posteriori Bayesian (MAPB) pharmacokinetic parameter estimation is an accurate and flexible method of estimating individual pharmacokinetic parameters using individual blood concentrations and prior information. In the past decade, many studies have developed optimal sampling strategies to estimate pharmacokinetic parameters as accurately as possible using either multiple regression analysis or MAPB estimation. This has been done for many drugs, especially immunosuppressants and anticancer agents. Methods of development for optimal sampling strategies (OSS) are diverse and heterogeneous. This review provides a comprehensive overview of OSS development methodology using MAPB pharmacokinetic parameter estimation, determines the transferability of published OSSs, and compares sampling strategies determined by MAPB estimation and multiple regression analysis. OSS development has the following components: 1) prior distributions; 2) reference value determination; 3) optimal sampling time identification; and 4) validation of the OSS. Published OSSs often lack all data necessary for the OSS to be clinically transferable. MAPB estimation is similar to multiple regression analysis in terms of predictive performance but superior in flexibility.

Evaluating performance of a decision support system to improve methotrexate pharmacotherapy in children and young adults with cancer

The management of high-dose methotrexate (MTX) therapy in patients with cancer depends on the routine monitoring of drug exposures in conjunction with leucovorin (LV), urine pH, patient hydration, and other clinical indices of patient well-being. A key factor in patient oversight is the facilitation of MTX clearance to minimize drug-related toxicity. The aim of this investigation was to evaluate the performance of a clinical decision support system and Bayesian forecasting algorithm in the prediction of MTX concentrations and assessment of LV dosing requirements in pediatric and young adult patients with cancer based on the current practice at the Children's Hospital of Philadelphia. Fifty patients ranging in age from 8 months to 21 years (weight range, 7.6-163.3 kg) contributing 80 total dosing events (183 MTX serum concentrations) were studied. The forecasting model was able to consistently predict future MTX concentrations with the knowledge of one prior concentration and continued to improve with additional concentration data made available through daily therapeutic drug monitoring. Precision was good at 12.9% with low bias at 2.2%. Comparison between the decision support system recommendations for LV rescue relative to the actual LV administration was also made. Sixteen patients would have initiated rescue therapy earlier, seven patients would have received a larger dose (42 smaller), and LV would have been given less often for 37 patients. The forecasting algorithm in the MTX dashboard was reasonably accurate in predicting MTX concentrations and should improve further as the underlying model and prediction algorithm evolves. This decision support system can be useful in helping physicians decide if a patient is clearing MTX as expected or if more aggressive rescue therapy is warranted.

High dose methotrexate treatment in children with acute lymphoblastic leukaemia may be optimised by a weight-based dose calculation

BACKGROUND

The inter-individual variation in exposure to methotrexate is considerable after intravenous high dose methotrexate (HDMTX) administration and both under- and over exposures may have dire consequences. Thus, optimal dose individualisation is of paramount importance.

PROCEDURE

We studied how pharmacokinetic parameters were related to outcome in 340 patients with acute lymphoblastic leukaemia (ALL). A population pharmacokinetic model was developed with data from 1284 HDMTX courses in 304 children evaluating age, height, weight, body surface area (BSA), sex, serum creatinine and serum alanine aminotransferase as potential covariates.

RESULT

Body weight improved the population pharmacokinetic model significantly more than any of the other patient characteristics, indicating that body weight may be the better way of dose normalisation. In a logistic regression analysis, higher values of clearance as well as volume of distribution were related to increased relapse risk in the standard (SR) and intermediate risk (IR) groups as well as in the entire cohort. A higher weight was strongly associated with worse outcome in the SR and IR groups, (P = 0.0186 and 0.0121, respectively).

CONCLUSIONS

We conclude that dose normalisation of methotrexate according to body weigh may give more predictable pharmacokinetics of methotrexate and may also improve the outcome for children with ALL.

Suspicion of drug-drug interaction between high-dose methotrexate and proton pump inhibitors: a case report - should the practice be changed?

We report a case of a potential drug-drug interaction in a woman treated by a first injection of high-dose methotrexate for a T-lymphoblastic lymphoma. Valaciclovir, fluoxetine and pantoprazole were given concomitantly. A methotrexate overdosage was shown at 36 h after infusion associated with a severe renal failure. Alkaline hyperhydration, folinic acid and carboxypeptidase G2 were given. Prescription analyses by pharmacists and literature research have permitted us to suggest that a drug-drug interaction between methotrexate and proton pump inhibitors (PPI) was responsible for this renal failure. Several mechanisms of interaction were suggested and might be related to the inhibition of renal methotrexate transporters by PPI, an increase in the methotrexate efflux to the blood by an upregulation of multidrug resistance protein 3 by PPI or genetic polymorphisms. This case shows that pharmacists can help physicians to optimize patient treatment: they consensually decided on the systematic discontinuation of PPI or a switch to ranitidine when patients were treated by high-dose methotrexate.

Influence of methotrexate exposure on outcome in patients treated with MBVP chemotherapy for primary central nervous system lymphoma

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

Although treated using the same high-dose methotrexate (HD-MTX)-based multiagent chemotherapy, patients with primary central nervous system lymphoma (PCNSL) have significant differences in outcome. However, little information has been published about factors influencing outcome in PCNSL. As it is known that the pharmacokinetics of MTX vary considerably between subjects leading to different exposure in patients receiving the same dose, it is important to evaluate its role in response to chemotherapy.

WHAT THIS STUDY ADDS

This study is the first to evaluate the exposure-response relationship in patients treated with MBVP chemotherapy. We found that patients who were early non-responders to MBVP chemotherapy had poor survival, whatever the salvage regimen. Tumour response at early evaluation was not associated with MTX pharmacokinetics and increasing the dose would probably not improve results.

AIMS

Although the standard treatment for primary central nervous system lymphoma (PCNSL) consists of three cycles of MBVP (methotrexate, BCNU, VP16, methylprednisolone) and radiotherapy, early failure of treatment may require modification of the treatment. However, our understanding of the outcome in such patients and of the factors involved in early failure of treatment is poor. In addition to known prognostic factors, we evaluated the influence of methotrexate (MTX) exposure on the response to MBVP chemotherapy in patients treated for PCNSL after the first two cycles.

METHODS

We retrospectively analyzed all patients with PCNSL treated with the MBVP regimen over the previous 10 years. Clinical, personal data and known prognostic factors were studied. The parameters of MTX exposure were estimated using a population pharmacokinetic approach with NONMEM. Objective response (OR), overall survival (OS) and failure-free survival (FFS) were evaluated in all patients.

RESULTS

Thirty-seven patients were studied. We observed lower FFS and OS (0.49 years) in patients who were not able to receive the planned treatment (group 1, n=12) than in those who received three cycles (8.04 years) (group 2, n=25). Known prognostic factors were comparable in both groups, but mean dose of MTX and mean AUC tended to be lower in patients who failed prematurely or showed no response after two cycles.

CONCLUSIONS

We found that patients who were early non-responders to MBVP chemotherapy had poor survival, without major influence of MTX exposure. It is thus probably unlikely that increasing the dose of MTX would improve outcome.

High dose methotrexate population pharmacokinetics and Bayesian estimation in patients with lymphoid malignancy

The purpose of present study was to develop a population pharmacokinetic model of high dose methotrexate (HD-MTX) infusion in patients with lymphoid malignancy, to investigate the biological and clinical covariates related to the drug distribution and elimination. It is also the purpose to propose a limited sampling strategy (LSS) for the estimation of the time above the threshold (0.2 micromol.L(-1)). A total 82 patients with lymphoid malignancy were involved in the study. A pharmacokinetic model was developed using nonlinear mixed-effect model. The influence of demographic characteristics, biological factors, and concurrent administration were investigated. The final predictive performance was validated by bootstrap and cross-validation. Bayesian estimation was evaluated. The pharmacokinetics of HD-MTX was described by a two-compartment model. The pharmacokinetic parameters and the inter-individual variability were as follows: the clearance CL, 7.45 L.h(-1) (inter-individual variability 50.6%), the volume of the central and peripheral compartment V(1), 25.9 L (22.5%), V(2), 9.23 L (97.8%), respectively, and the intercompartmental clearance Q, 0.333 L.h(-1) (70.4%). The influence of serum creatinine on CL and weight on V(1) was retained in the final model. The protocol involved one sampling time at 44 h after the start of the infusion, allowing one to predict the time at which the MTX concentration reached the expected threshold (0.2 micromol.L(-1)). Serum creatinine and weight showed significant influence on methotrexate CL and V(1), respectively. Furthermore, a Bayesian estimation based on the covariates and 44 h sample was developed, allowing prediction of the individual methotrexate pharmacokinetic parameters and the time to 0.2 micromol.L(-1).

Population Pharmacokinetics of High-Dose Methotrexate in Children with Acute Lymphoblastic Leukaemia

OBJECTIVE

To develop and a priori validate a methotrexate population pharmacokinetic model in children with acute lymphoblastic leukaemia (ALL), receiving high-dose methotrexate followed by folinic acid rescue, identifying the covariates that could explain part of the pharmacokinetic variability of methotrexate.

METHODS

The study was carried out in 49 children (aged 6 months to 17 years) who received high-dose methotrexate (3 g/m(2) per course) in long-term treatment. In an index group (37 individuals; 1236 methotrexate plasma concentrations), a population pharmacokinetic model was developed using a nonlinear mixed-effects model. The remaining patients' data (12 individuals; 278 methotrexate plasma concentrations) were used for model validation. Age, sex, total bodyweight (TBW), height, body surface area, lowest urine pH during infusion, serum creatinine, ALT, AST, folinic acid dose and length of rescue were analysed as possible covariates. The final predictive performance of the pharmacokinetic model was tested using standardised mean prediction errors.

RESULTS

The final population pharmacokinetic model (two-compartmental) included only age and total bodyweight as influencing clearance (CL) and volume of distribution of central compartment (V(1)). For children aged < or =10 years: CL (L/h) = 0.287 . TBW(0.876); V(1) (L) = 0.465 . TBW, and for children aged >10 years: CL (L/h) = 0.149 . TBW; V(1) (L) = 0.437 . TBW. From the base to the final model, the inter-individual variabilities for CL and V(1) were significantly reduced in both age groups (30-50%). The coefficients of variation of the pharmacokinetic parameters were <30%, while residual and inter-occasional coefficients maintained values close to 40%. Validation of the proposed model revealed the suitability of the model.

CONCLUSION

A methotrexate population pharmacokinetic model has been developed for ALL children. The proposed model could be used in Bayesian algorithms with a limited sampling strategy to estimate the systemic exposure of individual patients to methotrexate and adapt both folinic acid rescue and methotrexate dosing accordingly.