Evidence map›Paper›PMID 39257396›Full record

ArticleFrontiers in pharmacology2024

Population pharmacokinetics study of tacrolimus in liver transplant recipients: a comparison between patients with or without liver cancer before surgery.

Haihong Bai, Juping Yun, Zihe Wang, Yingmin Ma, Wei Liu

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Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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  5. Frontiers in pharmacology · 2026
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Haihong BaiDepartment of Pharmacy, Beijing YouAn Hospital of Capital Medical University, Beijing, China.
Juping YunDepartment of Pharmacy, Beijing YouAn Hospital of Capital Medical University, Beijing, China.
Zihe WangDepartment of Pharmacy, Beijing YouAn Hospital of Capital Medical University, Beijing, China.
Yingmin MaDepartment of Respiratory and Critical Care Medicine, Beijing YouAn Hospital of Capital Medical University, Beijing, China.
Wei LiuDepartment of Pharmacy, Beijing YouAn Hospital of Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: The main challenge for immunosuppressive therapy using tacrolimus in liver transplantation is the considerable variability in its oral bioavailability and the narrow treatment range. Many population pharmacokinetic (PopPK) models have been established to precisely estimate the PK variability of tacrolimus in liver transplant recipients. However, it remains unclear whether there is a significant difference in the PK behavior of tacrolimus between patients with or without liver cancer before surgery. Therefore, we aimed to compare the differences of PK parameters and simulate exposures of tacrolimus between populations preoperatively diagnosed with liver cancer or not by PopPK modeling. Methods: In total, 802 blood concentrations of tacrolimus from 196 patients (118 liver cancer and 78 non-liver-cancer samples) were included in this study. Demographic data and clinical parameters were integrated to perform a PopPK analysis using the nonlinear mixed-effects modeling approach. Potential covariates were evaluated by using a stepwise method. Goodness-of-fit plot and bootstrap were performed to assess the model stability and predictive performance. Simulations were introduced to optimize dosing regimens of both the liver cancer and non-liver-cancer groups according to the guidance. Results: The PK of tacrolimus was best described by a one-compartment model with first-order absorption and linear elimination, with weight and direct bilirubin as the significant covariates. In the process of constructing the basic model, we tried to separately estimate the PK parameters in liver cancer and non-liver-cancer populations. The results showed that the PK parameters in the two populations were similar, and the individual variation in Ka in non-liver-cancer subjects was large. Hence, the final model did not distinguish between the two populations. Moreover, a minor increase of less than 10% was observed in the simulated exposure in the patients preoperatively diagnosed with liver cancer compared with that in non-liver-cancer groups. Conclusion: The established PopPK model was capable of optimizing tacrolimus dosing in whole populations who underwent liver transplantation. Although a minimal difference was found in tacrolimus exposure between the liver cancer and non-liver-cancer groups, more research is warranted to explore the differences between the two populations in the future, given the potential limitations of this study.

Indexed as

liver cancerliver transplantationpopulation pharmacokineticstacrolimustherapeutic drug monitoring

Identifiers

PMID39257396
PMCPMC11385303

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