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他克莫司在突尼斯肾移植患者中的给药算法:CYP3A4*1B 和 CYP3A4*22 多态性的影响。

Dosing algorithm for Tacrolimus in Tunisian Kidney transplant patients: Effect of CYP 3A4*1B and CYP3A4*22 polymorphisms.

机构信息

Laboratory of Pharmacology, Faculty of Medicine, University of Monastir, Tunisia.

Laboratory of Pharmacology, Faculty of Medicine, University of Monastir, Tunisia; Faculty of Sciences of Bizerte, Carthage University, Tunisia.

出版信息

Toxicol Appl Pharmacol. 2020 Nov 15;407:115245. doi: 10.1016/j.taap.2020.115245. Epub 2020 Sep 17.

Abstract

Prescribing appropriate Tacrolimus (Tac) dosing is still a challenge for clinicians due to the interindividual variability in dose requirement and the narrow therapeutic index. Our objective is to identify potential factors that affects Tac exposure in Tunisian Kidney patients and to develop and validate a Tac dose requirement algorithm including genetic and nongenetic variables. A cross-sectional study was performed. To assess the implication of each covariate on Tac exposure, we classified the patients according to quartiles of exposure index (trough Tac concentration/Dose: C0/D). The total population was divided into the building (75%) and validation (25%) groups. Multiple linear regression was applied to determine the algorithm of Tac dose including the patient's genetic and nongenetic variables. A total of 685 samples issued from 102 kidney transplant patients were included in the study. The post-transplant time (PT), ATG therapy, CYP3A4, and CYP3A5 polymorphisms were significantly associated with trough Tac C0/D. However, the age, sex, body weight, and induction by basiliximab did not show any effect on C0/D. Predicted Tac dose was calculated as follows: Tac Dose = - 2,725 - (10 * PT day) + (0,09weight) + (1,40ATG) + (2,09* CYP3A41B allele) + (0,88gender) + (0,05Age) + (1,10CYP3A422 allele) + (2,30 target ranges). Our study designed the first algorithm that predicts the Tac dose requirement in Tunisian Kidney transplant patients including genetic and non-genetic factors. The application of such an algorithm should reduce the number of patients with Tac trough concentration outside the target range and could minimize the time to reach a therapeutic C0.

摘要

由于剂量需求的个体间差异和治疗指数狭窄,为临床医生开具合适的他克莫司(Tac)剂量仍然是一个挑战。我们的目标是确定影响突尼斯肾移植患者 Tac 暴露的潜在因素,并开发和验证包括遗传和非遗传变量的 Tac 剂量需求算法。进行了一项横断面研究。为了评估每个协变量对 Tac 暴露的影响,我们根据暴露指数(谷浓度 Tac/剂量:C0/D)的四分位数对患者进行分类。将总人群分为构建(75%)和验证(25%)组。应用多元线性回归确定包括患者遗传和非遗传变量在内的 Tac 剂量算法。共有 102 名肾移植患者的 685 个样本纳入本研究。移植后时间(PT)、ATG 治疗、CYP3A4 和 CYP3A5 多态性与 Tac C0/D 显著相关。然而,年龄、性别、体重和巴利昔单抗诱导对 C0/D 没有影响。预测 Tac 剂量计算如下:Tac 剂量=-2725-(10PT 天)+(0.09体重)+(1.40ATG)+(2.09CYP3A41B 等位基因)+(0.88性别)+(0.05年龄)+(1.10CYP3A422 等位基因)+(2.30目标范围)。我们的研究设计了第一个预测突尼斯肾移植患者 Tac 剂量需求的算法,包括遗传和非遗传因素。应用这种算法可以减少 Tac 谷浓度超出目标范围的患者数量,并可以最大限度地缩短达到治疗 C0 的时间。

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