Background
High-dose methotrexate (HDMTX) represents an important treatment modality in several pediatric cancers, though managing toxicities with HDMTX continues to be a challenge. Due to its narrow therapeutic window as well as significant variability in its pharmacokinetics, the current management of the MTX therapy is complicated. Urine alkalinization, vigorous hydration, and rescue with leucovorin are used to minimize the toxicities associated with this drug. MTX concentrations are routinely measured to decide when to stop leucovorin rescue but not to individualize future doses. Despite incorporating these measures, the incidence of life-threatening toxicity continues to occur in approximately 1%. A better understanding of the pharmacokinetics (PK) of MTX could be helpful in improving the management of MTX therapy. The objectives of this analysis were 1) to develop a population pharmacokinetic model of HDMTX in pediatric cancer patients from routine clinical data and 2) to utilize the population approach as a tool to evaluate the predictable PK variability of MTX.
Methods
A standard-of-care design yielded a total of 956 concentrations collected from 56 patients. Patients were administered MTX by IV infusion (doses from 1 to 12 g/m2) on up to 12 occasions. Data were analyzed using NONMEM 7.2. A two compartment model with first order elimination was parameterized in terms of clearance (CL), central volume of distribution (V1), intercompartmental clearance (Q) and peripheral volume of distribution (V2). Size related differences in CL, V1, Q and V2 were accounted for by theory based allometric scaling (1) using total body weight (TBW) and fat free mass (FFM) (2) to account for body composition. Creatinine clearance (CLcr) was predicted using the Schwartz formulae (3-6). Clearance (CL) was split into a component that varied with urine pH (renal clearance tubular, CLtub) and a component that varied with glomerular function (renal clearance glomerular, CLgfr) predicted from the ratio of creatinine clearance (CLcr) to normal glomerular filtration rate based on age and FFM (7). Random between subject (BSV) and between occasion (BOV) variability was estimated assuming a log-normal distribution of total CL (sum of CLtub and CLgfr), V1, Q and V2 after accounting for predictable (fixed effect) differences using TBW, FFM, urine pH and renal function. The covariance between CL, V1, Q and V2 for BSV and for BOV were included in the full model. Residual unidentified variability (RUV) was described by a proportional residual error model. Model selection was based on improvement in objective function.
Results
Between subject differences in clearance were predicted by size and renal function. TBW was the best size predictor for CL, V1 and V2 while fat free mass was best for Q. There was no significant improvement from using urine pH to predict clearance. The population mean parameters and their associated precision (%RSE) for CLtub, CLgfr, central volume of distribution, inter-compartmental clearance, and peripheral distribution volume were estimated to be 19.0 (19.1%) L/h/70kg, 5.4 (28.6%) L/h/70kg, 145.0 (20.8%) L/70kg, 0.9 (26.1%) L/h/70kg and 22.3 (33.7%) L/70kg, respectively. In the final model the BSV in CL was 65% and BOV in CL was 56%. 20% of total population variance in CL (BSV and BOV) was explained by differences in total body weight. Only 3% of variance in CL was explained by differences in renal function.
Conclusion
Size, but not body composition differences can predict some of the differences in MTX clearance. Serum creatinine has no clinically relevant value in predicting MTX clearance in a typical population requiring HDMTX.
References
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