10.6084/M9.FIGSHARE.19681464.V1
Min Zhan
Min
Zhan
Yiqi Sun
Yiqi
Sun
Fang Zhou
Fang
Zhou
Honghong Wang
Honghong
Wang
Zebin Chen
Zebin
Chen
Lianzhen Yan
Lianzhen
Yan
Xingang Li
Xingang
Li
Population pharmacokinetics of methotrexate in paediatric patients with acute lymphoblastic leukaemia and malignant lymphoma
<p></p><p>This study aimed to identify physiological and pharmacogenomic covariates and develop a population pharmacokinetic model of high-dose methotrexate (HD-MTX) in Chinese paediatric patients with acute lymphoblastic leukaemia (ALL) and malignant lymphoma.</p><p>A total of 731 MTX courses and 1658 MTX plasm concentrations from 205 paediatric patients with ALL and malignant lymphoma were analysing using a non-linear mixed-effects model technique. 47 SNPs in 16 MTX-related genes 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.</p><p>Two-compartmental model with allometric scaling using BSA could nicely characterise the <i>in vivo</i> behaviour 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)<sup>0.75</sup> * e<sup>0.13*rs17004785</sup> * e<sup>0.39*rs4148416</sup> * e<sup>ηCL</sup>, Vc = 24.98 * (BSA/1.73) * e<sup>ηvc</sup>, <i>Q</i> = 0.18 * (BSA/1.73)<sup>0.75</sup> * e<sup>ηQ</sup> and Vp = 4.70 * (BSA/1.73) * e<sup>ηvp</sup>.</p><p>The established model combined with the Bayesian approach could estimate individual pharmacokinetic parameters and optimise personalised HD-MTX therapy for paediatric patients with ALL and malignant lymphoma.</p><p></p> <p>This study aimed to identify physiological and pharmacogenomic covariates and develop a population pharmacokinetic model of high-dose methotrexate (HD-MTX) in Chinese paediatric patients with acute lymphoblastic leukaemia (ALL) and malignant lymphoma.</p> <p>A total of 731 MTX courses and 1658 MTX plasm concentrations from 205 paediatric patients with ALL and malignant lymphoma were analysing using a non-linear mixed-effects model technique. 47 SNPs in 16 MTX-related genes 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.</p> <p>Two-compartmental model with allometric scaling using BSA could nicely characterise the <i>in vivo</i> behaviour 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)<sup>0.75</sup> * e<sup>0.13*rs17004785</sup> * e<sup>0.39*rs4148416</sup> * e<sup>ηCL</sup>, Vc = 24.98 * (BSA/1.73) * e<sup>ηvc</sup>, <i>Q</i> = 0.18 * (BSA/1.73)<sup>0.75</sup> * e<sup>ηQ</sup> and Vp = 4.70 * (BSA/1.73) * e<sup>ηvp</sup>.</p> <p>The established model combined with the Bayesian approach could estimate individual pharmacokinetic parameters and optimise personalised HD-MTX therapy for paediatric patients with ALL and malignant lymphoma.</p>
Medicine
Genetics
Ecology
Biological Sciences not elsewhere classified
Cancer
Hematology
Plant Biology
Taylor & Francis
2022
2022-04-29
2024-02-15
Journal contribution
31388 Bytes
10.6084/m9.figshare.19681464
10.1080/00498254.2022.2069060
CC BY 4.0