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Clinical covariates that improve the description of high dose methotrexate pharmacokinetics in a diverse population to inform MTXPK.org

Authors :
Zachary L. Taylor
Tamara P. Miller
Ethan A. Poweleit
Nicholas P. DeGroote
Lauren Pommert
Oluwafunbi Awoniyi
Sarah G. Board
Ngozi Ugboh
Vivek Joshi
Nick Ambrosino
Ashley Chavana
Melanie B. Bernhardt
Eric S. Schafer
Maureen M. O'Brien
Sharon M. Castellino
Laura B. Ramsey
Source :
Clinical and Translational Science, Vol 16, Iss 11, Pp 2130-2143 (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract The MTXPK.org webtool was launched in December 2019 and was developed to facilitate model‐informed supportive care and optimal use of glucarpidase following the administration of high‐dose methotrexate (HDMTX). One limitation identified during the original development of the MTXPK.org tool was the perceived generalizability because the modeled population comprised solely of Nordic pediatric patients receiving 24‐h infusions for the treatment of acute lymphoblastic leukemia. The goal of our study is to describe the pharmacokinetics of HDMTX from a diverse patient population (e.g., races, ethnicity, indications for methotrexate, and variable infusion durations) and identify meaningful factors that account for methotrexate variability and improve the model's performance. To do this, retrospectively analyzed pharmacokinetic and toxicity data from pediatric and adolescent young adult patients who were receiving HDMTX (>0.5 g/m2) for the treatment of a cancer diagnosis from three pediatric medical centers. We performed population pharmacokinetic modeling referencing the original MTXPK.org NONMEM model (includes body surface area and serum creatinine as covariates) on 1668 patients, 7506 administrations of HDMTX, and 30,250 concentrations. Our results support the parameterizations of short infusion duration (

Details

Language :
English
ISSN :
17528062 and 17528054
Volume :
16
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Clinical and Translational Science
Publication Type :
Academic Journal
Accession number :
edsdoj.5f03661676c74213b95f1b9c76080e52
Document Type :
article
Full Text :
https://doi.org/10.1111/cts.13600