Literature DB >> 32949580

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

Nadia Ben-Fredj1, Ibtissem Hannachi2, Zohra Chadli1, Haifa Ben-Romdhane1, Naceur A Boughattas1, Najah Ben-Fadhel1, Karim Aouam1.   

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 - (10-3 * PT day) + (0,09*weight) + (1,40*ATG) + (2,09* CYP3A4*1B allele) + (0,88*gender) + (0,05*Age) + (1,10*CYP3A4*22 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.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CYP3A polymorphisms; Dosing algorithm; Tacrolimus

Year:  2020        PMID: 32949580     DOI: 10.1016/j.taap.2020.115245

Source DB:  PubMed          Journal:  Toxicol Appl Pharmacol        ISSN: 0041-008X            Impact factor:   4.219


  3 in total

1.  Composite CYP3A phenotypes influence tacrolimus dose-adjusted concentration in lung transplant recipients.

Authors:  Michelle Liu; Ciara M Shaver; Kelly A Birdwell; Stephanie A Heeney; Christian M Shaffer; Sara L Van Driest
Journal:  Pharmacogenet Genomics       Date:  2022-04-07       Impact factor: 2.000

2.  Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients.

Authors:  Lekshmy Srinivas; Noble Gracious; Radhakrishnan R Nair
Journal:  Front Pharmacol       Date:  2021-11-30       Impact factor: 5.810

3.  Tacrolimus Concentration Is Effectively Predicted Using Combined Clinical and Genetic Factors in the Perioperative Period of Kidney Transplantation and Associated with Acute Rejection.

Authors:  Fang Cheng; Qiang Li; Zheng Cui; Zhendi Wang; Fang Zeng; Yu Zhang
Journal:  J Immunol Res       Date:  2022-09-09       Impact factor: 4.493

  3 in total

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