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Yang Y, Liu Z, Chen J, Wang X, Jiao Z, Wang Z. Factors influencing methotrexate pharmacokinetics highlight the need for individualized dose adjustment: a systematic review. Eur J Clin Pharmacol 2024; 80:11-37. [PMID: 37934204 DOI: 10.1007/s00228-023-03579-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 10/07/2023] [Indexed: 11/08/2023]
Abstract
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.
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Affiliation(s)
- Yunyun Yang
- Department of Pharmacy, Shanghai Changhai Hospital, the First Affiliated Hospital of Navy Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Zhengyue Liu
- Department of Pharmacy, Shanghai Changhai Hospital, the First Affiliated Hospital of Navy Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Jingxia Chen
- Department of Pharmacy, Shanghai Changhai Hospital, the First Affiliated Hospital of Navy Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Xuebin Wang
- Department of Pharmacy, Shanghai Changhai Hospital, the First Affiliated Hospital of Navy Medical University, 168 Changhai Rd, Shanghai, 200433, China
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241 Huaihai West Road, Shanghai, 200030, China.
| | - Zhuo Wang
- Department of Pharmacy, Shanghai Changhai Hospital, the First Affiliated Hospital of Navy Medical University, 168 Changhai Rd, Shanghai, 200433, China.
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Methaneethorn J, AlEjielat R, Leelakanok N. Factors influencing methotrexate and methotrexate polyglutamate in patients with rheumatoid arthritis: a systematic review of population pharmacokinetics. Drug Metab Pers Ther 2022; 37:229-240. [PMID: 35218177 DOI: 10.1515/dmpt-2021-0190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 12/18/2021] [Indexed: 11/15/2022]
Abstract
Low dose methotrexate (MTX) is commonly used in the treatment of rheumatoid arthritis. The clinical effect is mediated by its metabolite, methotrexate polyglutamate (MTX-PGn). The drug exhibits high interindividual pharmacokinetic variability and the optimal MTX dose is different among individuals. Thus, several MTX population pharmacokinetic (PopPK) models were developed to characterize factors affecting MTX pharmacokinetic variability. This review summarizes significant predictors for MTX pharmacokinetics and identifies knowledge gaps to be further examined. A total of 359 articles were identified from a systematic search of four databases: PubMed, Science Direct, and CINAHL Complete. Of these eight studies were included. Most studies investigated influential factors on MTX pharmacokinetics, but information on MTX-PGn is limited, with only one study performing a parent-metabolite (MTX-PG3) model. MTX pharmacokinetics was described using a two-compartment model with first-order elimination in most studies, with the MTX clearance ranging from 6.94 to 12.39 L/h. Significant predictors influencing MTX clearance included weight, creatinine clearance, sex, OATP1B3 polymorphism, and MTX multiple dosing. While body mass index and red blood cell counts were significant predictors for MTX-PG3 clearance. Providing that MTX-PGn plays a crucial role in clinical effect, further studies should determine other factors affecting MTX-PGn as well as its relationship with clinical response.
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Affiliation(s)
- Janthima Methaneethorn
- Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, Thailand.,Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, Thailand
| | - Rowan AlEjielat
- Faculty of Pharmacy and Medical Sciences, University of Petra, Amman, Jordan
| | - Nattawut Leelakanok
- Department of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Burapha University, Chonburi, Thailand
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Zhang Y, Sun L, Chen X, Zhao L, Wang X, Zhao Z, Mei S. A Systematic Review of Population Pharmacokinetic Models of Methotrexate. Eur J Drug Metab Pharmacokinet 2022; 47:143-164. [PMID: 34985725 DOI: 10.1007/s13318-021-00737-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2021] [Indexed: 01/23/2023]
Abstract
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.
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Affiliation(s)
- Yiming Zhang
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Fengtai District, Beijing, 100070, People's Republic of China.,Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Liyu Sun
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Fengtai District, Beijing, 100070, People's Republic of China.,Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Xinwei Chen
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China.,Department of Pharmacy, Beijing Children's Hospital, National Center for Children's Health, Capital Medical University, Beijing, 100045, People's Republic of China
| | - Libo Zhao
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China.,Department of Pharmacy, Beijing Children's Hospital, National Center for Children's Health, Capital Medical University, Beijing, 100045, People's Republic of China
| | - Xiaoling Wang
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China.,Department of Pharmacy, Beijing Children's Hospital, National Center for Children's Health, Capital Medical University, Beijing, 100045, People's Republic of China
| | - Zhigang Zhao
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Fengtai District, Beijing, 100070, People's Republic of China. .,Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China.
| | - Shenghui Mei
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Fengtai District, Beijing, 100070, People's Republic of China. .,Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China.
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Induction of EMT-like phenotypes by an active metabolite of leflunomide and its contribution to pulmonary fibrosis. Cell Death Differ 2010; 17:1882-95. [PMID: 20489727 DOI: 10.1038/cdd.2010.64] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Drug-induced interstitial lung disease (ILD), particularly pulmonary fibrosis, is a serious clinical concern and myofibroblasts have been suggested to have a major role, with it recently being revealed that some of these myofibroblasts are derived from lung epithelial cells through epithelial-mesenchymal transition (EMT). In this study, we examined the EMT-inducing abilities of drugs known to induce ILD clinically. EMT-like phenotypes were induced by A771726, an active metabolite of leflunomide having an inhibitory effect on dihydroorotate dehydrogenase (DHODH). Smad-interacting protein 1 (a transcription factor regulating EMT) and the Notch-signaling pathway but not transforming growth factor-β was shown to be involved in A771726-induced EMT-like phenotypes. When the cultures were supplemented with exogenous uridine, the A771726-induced EMT-like phenotypes and activation of the Notch-signaling pathway disappeared. Similarly, an A771726 analog without inhibitory activity on DHODH produced no induction, suggesting that this process is mediated through the inhibition of DHODH. In vivo, administration of leflunomide stimulated bleomycin-induced EMT-like phenomenon in pulmonary tissue, and exacerbated bleomycin-induced pulmonary fibrosis, both of which were suppressed by coadministration of uridine. Taken together, these findings suggest that leflunomide-dependent exacerbation of bleomycin-induced pulmonary fibrosis is mediated by stimulation of EMT of lung epithelial cells, providing the first evidence that drug-induced pulmonary fibrosis involves EMT of these cells.
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