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曲面积/谷浓度比值可否用于优化他克莫司个体化剂量调整?

Can the Area Under the Curve/Trough Level Ratio Be Used to Optimize Tacrolimus Individual Dose Adjustment?

机构信息

Service de Pharmacologie, Toxicologie et Pharmacovigilance, Centre de Biologie et de Recherche en Santé, Centre Hospitalier Universitaire de Limoges, Limoges, France.

Department of Pharmacology and Transplantation, UMR1248 Université de Limoges, INSERM, Limoges, France.

出版信息

Transplantation. 2023 Jan 1;107(1):e27-e35. doi: 10.1097/TP.0000000000004405. Epub 2022 Nov 2.

DOI:10.1097/TP.0000000000004405
PMID:36508648
Abstract

BACKGROUND

The aim of this work was to evaluate, in a large data set of renal transplant recipients, the intraindividual variability of the area under the curve (AUC)/predose concentration (C0) ratio in comparison with that of AUC, C0, AUC/dose, and C0/dose.

METHODS

Patients with at least 2 tacrolimus AUC estimation requests were extracted from the Immunosuppressant Bayesian dose Adjustment website, and relative variations between 2 consecutive visits for the different metrics were calculated and compared.

RESULTS

Data from 1325 patients on tacrolimus (3827 measured C0 and estimated AUC) showed that the lowest mean relative variation between 2 consecutives visits was for the AUC/C0 ratio (95% confidence interval [CI] relative fold change = -43% to 44% for AUC/C0; 95% CI, -77% to 72% for AUC; 95% CI, -82% to 98% for AUC/dose; 95% CI, -81% to 80% for C0 and 95% CI, -94% to 117% for C0/dose. The correlation between 2 consecutive requests, whether close or far apart, was also best for the AUC/C0 ratio ( r  = 0.33 and r  = 0.34, respectively) in comparison with C0 ( r  = 0.21 and r  = 0.22, respectively) and AUC ( r  = 0.19 and 0.28, respectively). Regression analysis between AUC0-24 and C0 showed that for some patients, the usual C0 targets translated into some very unusual AUC values. As the AUC/C0 ratio is quite stable during large periods, individualized C0 targets can be derived from the AUC targets, and an algorithm that estimates the individualized C0 was developed for situations in which prior AUC estimates are available or not.

CONCLUSIONS

In this study, we confirmed in a large data set that the AUC/C0 ratio yields low intraindividual variability, whereas C0 shows the largest, and we propose to calculate individualized C0 targets based on this ratio.

摘要

背景

本研究旨在评估在一个大型肾移植受者的数据集内,与 AUC、C0、AUC/剂量和 C0/剂量相比,AUC/浓度(C0)比值的个体内变异性。

方法

从免疫抑制剂贝叶斯剂量调整网站中提取至少有 2 次他克莫司 AUC 估计请求的患者数据,并计算和比较不同指标两次连续就诊之间的相对变化。

结果

在 1325 例接受他克莫司治疗的患者(3827 例测量的 C0 和估计的 AUC)中,两次连续就诊之间的平均相对变化最小的是 AUC/C0 比值(AUC/C0 的 95%置信区间[CI]相对折叠变化为-43%至 44%;AUC 的 95%CI 为-77%至 72%;AUC/剂量的 95%CI 为-82%至 98%;C0 的 95%CI 为-81%至 80%;C0/剂量的 95%CI 为-94%至 117%。两次连续请求之间的相关性,无论是接近还是相距甚远,对于 AUC/C0 比值(r 分别为 0.33 和 0.34)也都优于 C0(r 分别为 0.21 和 0.22)和 AUC(r 分别为 0.19 和 0.28)。AUC0-24 与 C0 之间的回归分析表明,对于某些患者,常用的 C0 目标转化为一些非常不寻常的 AUC 值。由于 AUC/C0 比值在很长一段时间内相当稳定,可以根据 AUC 目标推导出个体化的 C0 目标,并且针对存在或不存在先前 AUC 估计值的情况开发了一种估算个体化 C0 的算法。

结论

在这项研究中,我们在一个大型数据集内证实,AUC/C0 比值具有较低的个体内变异性,而 C0 的变异性最大,我们建议基于此比值计算个体化的 C0 目标。

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