在无类固醇肾移植患者的浓度-时间曲线下预测霉酚酸和他克莫司面积的有限抽样策略

IF 2.7 4区 医学 Q2 PHARMACOLOGY & PHARMACY
Katrine Agergaard, Helle C. Thiesson, Jan Carstens, Christine E. Staatz, Erkka Järvinen, Flemming Nielsen, Heidi Dahl Christensen, Rikke Juul-Sandberg, Kim Brøsen, Tore Bjerregaard Stage, Maria C. Kjellsson, Troels K. Bergmann
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引用次数: 0

摘要

本研究旨在制定有限的采样策略,以预测稳定无类固醇肾移植患者从一到三个血液样本中口服麦考酚酸(MPA)暴露,并评估相同的方案是否可以预测他克莫司暴露。此外,我们的目的是验证现有的策略,并在我们的队列中描述MPA及其无活性代谢物MPA-葡糖苷(MPAG)的药代动力学。我们分析了来自15名无类固醇肾移植患者的密集药代动力学抽样数据,这些患者被前瞻性地纳入更大队列的一部分。采用LC-MS分析血浆(MPA、MPAG)和全血(他克莫司)药物浓度。暴露(AUC0-12h)基于非室室分析(MPA, MPAG)或模型衍生(他克莫司)。使用多元逐步线性回归分析制定有限抽样策略,并使用Bland-Altman分析评估偏差和不精度。MPA、MPAG和他克莫司的中位AUC0-12h分别为31.2、346.6和81.9 ng/mL·h。有限的采样策略,包括测量C0和C1.5,或C0, C0.5和C1.5,可以预测MPA和他克莫司AUC0-12h低(< 15%)的偏差和不精确。上述策略均不能充分预测MPA AUC0-12h。MPA和他克莫司的有限采样策略可能取代无类固醇肾移植患者的完整药代动力学分析。在实现之前需要进行外部验证。肾移植患者在移植器官的整个生命周期内都接受免疫抑制药物治疗。在这项研究中,我们的目的是推导数学方程,可以同时预测这两种药物(他克莫司和霉酚酸酯)的总口服药物暴露基于少数血液样本。我们分析了15名患者血液样本中的药物浓度,计算了他们的暴露量,并评估了数学方程预测暴露量的准确性。我们可以从两个或三个样本中预测总药物暴露,这些方程可以用于未来的研究和临床,以确保适当的免疫抑制水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Limited Sampling Strategies to Predict Mycophenolic Acid and Tacrolimus Area Under the Concentration–Time Curve in Steroid-Free Kidney Transplant Patients

Limited Sampling Strategies to Predict Mycophenolic Acid and Tacrolimus Area Under the Concentration–Time Curve in Steroid-Free Kidney Transplant Patients

This study aimed to develop limited sampling strategies to predict oral mycophenolic acid (MPA) exposure from one to three blood samples in stable steroid-free kidney-transplanted patients and assess if the same scheme could predict tacrolimus exposure. Additionally, we aimed to validate existing strategies, and to describe the pharmacokinetics of MPA and its inactive metabolite, MPA-glucuronide (MPAG), in our cohort. We analysed data from dense pharmacokinetic sampling from 15 steroid-free kidney-transplanted patients, which were prospectively enrolled as part of larger cohort. Drug concentration was analysed in plasma (MPA, MPAG) or in whole blood (tacrolimus) using LC–MS. Exposure (AUC0-12h) was based on non-compartmental analysis (MPA, MPAG) or model-derived (tacrolimus). Limited sampling strategies were developed using multiple stepwise linear regression analysis and evaluated for bias and imprecision and using Bland–Altman analysis. Median AUC0-12h was 31.2 μg/mL·h, 346.6 μg/mL·h and 81.9 ng/mL·h for MPA, MPAG and tacrolimus, respectively. Limited sampling strategies incorporating measurements at C0 and C1.5, or at C0, C0.5 and C1.5 could predict MPA and tacrolimus AUC0-12h with low (< 15%) bias and imprecision. None of the previous strategies could adequately predict MPA AUC0-12h. Limited sampling strategies for MPA and tacrolimus can potentially replace full pharmacokinetic profiling in steroid-free kidney transplant patients. External validation is needed before implementation.

Summary

Kidney-transplanted patients are treated with immunosuppressive drugs throughout the lifespan of the transplanted organ. In this study, we aimed to derive mathematical equations that can simultaneously predict the total oral drug exposure of two of these drugs (tacrolimus and mycophenolate mofetil) based on few blood samples. We analysed drug concentration in blood samples from 15 patients, calculated their exposure and assessed how accurately the mathematical equations could predict the exposure. We could predict the total drug exposure from two or three samples, and these equations can be used in future research and in the clinic to ensure proper immunosuppressive levels.

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来源期刊
CiteScore
5.60
自引率
6.50%
发文量
126
审稿时长
1 months
期刊介绍: Basic & Clinical Pharmacology and Toxicology is an independent journal, publishing original scientific research in all fields of toxicology, basic and clinical pharmacology. This includes experimental animal pharmacology and toxicology and molecular (-genetic), biochemical and cellular pharmacology and toxicology. It also includes all aspects of clinical pharmacology: pharmacokinetics, pharmacodynamics, therapeutic drug monitoring, drug/drug interactions, pharmacogenetics/-genomics, pharmacoepidemiology, pharmacovigilance, pharmacoeconomics, randomized controlled clinical trials and rational pharmacotherapy. For all compounds used in the studies, the chemical constitution and composition should be known, also for natural compounds.
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