Literature DB >> 16044097

Population pharmacokinetic estimation of tacrolimus apparent clearance in adult liver transplant recipients.

Hamim Zahir1, Andrew J McLachlan, Ameeta Nelson, Geof McCaughan, Margaret Gleeson, Fatemeh Akhlaghi.   

Abstract

The goal was to study the factors affecting tacrolimus apparent clearance (CL/F) in adult liver transplant recipients. Tacrolimus dose and concentration data (n = 694) were obtained from 67 liver transplant recipients (22 female and 45 male), and the data were analyzed using a nonlinear mixed-effect modeling (NONMEM) method. A 1-compartment pharmacokinetic model with first-order elimination, an absorption rate constant fixed at 4.5 hours, and first-order conditional estimation was used to describe tacrolimus disposition. The predictive performance of the final model was evaluated using data splitting and assessing bias and precision of the estimates. The population estimate of tacrolimus CL/F and apparent volume of distribution (V/F) were found to be 21.3 L/h (95% confidence interval, CI, 18.0-24.6 L/h) and 316.1 L (95% CI 133-495 L), respectively. Neither patient's age, weight, gender, nor markers of liver function influenced tacrolimus CL/F. The final model was TVCL = 21.3 + 9.8 x (1 - HEM) + 3.4 x (1 - ALB) - 2.1 x (1 - DIL) - 7.4 x (1 - FLU), where TVCL, typical estimate of apparent clearance, HEM = 0 if hematocrit <35%, otherwise 1; ALB = 0 if albumin <3.5 g/dL, otherwise 1; DIL = 0 if diltiazem is coadministered, otherwise 1; FLU = 0 if fluconazole is coadministered, otherwise 1. This study identified the factors that significantly affect tacrolimus disposition in adult liver transplant recipients during the early posttransplantation period. This information will be helpful to clinicians for dose individualization of tacrolimus in liver transplant recipients with different clinical conditions including anemia or hypoalbuminemia or in those patients receiving diltiazem or fluconazole.

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Year:  2005        PMID: 16044097     DOI: 10.1097/01.ftd.0000170029.36573.a0

Source DB:  PubMed          Journal:  Ther Drug Monit        ISSN: 0163-4356            Impact factor:   3.681


  14 in total

1.  Tacrolimus pharmacokinetics in the early post-liver transplantation period and clinical applicability via Bayesian prediction.

Authors:  Itziar Oteo; John C Lukas; Nerea Leal; Elena Suarez; Andres Valdivieso; Mikel Gastaca; Jorge Ortiz de Urbina; Rosario Calvo
Journal:  Eur J Clin Pharmacol       Date:  2012-06-03       Impact factor: 2.953

2.  Pharmacokinetic study of tacrolimus in cystic fibrosis and non-cystic fibrosis lung transplant patients and design of Bayesian estimators using limited sampling strategies.

Authors:  Franck Saint-Marcoux; Christiane Knoop; Jean Debord; Philippe Thiry; Annick Rousseau; Marc Estenne; Pierre Marquet
Journal:  Clin Pharmacokinet       Date:  2005       Impact factor: 6.447

3.  Prediction tacrolimus blood levels based on the Bayesian method in adult kidney transplant patients.

Authors:  Marie Antignac; Christine Fernandez; Benoît Barrou; Mariona Roca; Jean-Louis Favrat; Saïk Urien; Robert Farinotti
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2011-02-24       Impact factor: 2.441

4.  Pathophysiological idiosyncrasies and pharmacokinetic realities may interfere with tacrolimus dose titration in liver transplantation.

Authors:  Itziar Oteo; John C Lukas; Nerea Leal; Elena Suarez; Andres Valdivieso; Mikel Gastaca; Jorge Ortiz de Urbina; Rosario Calvo
Journal:  Eur J Clin Pharmacol       Date:  2011-02-17       Impact factor: 2.953

5.  Population pharmacokinetic analysis of tacrolimus in the first year after pediatric liver transplantation.

Authors:  V Guy-Viterbo; A Scohy; R K Verbeeck; R Reding; P Wallemacq; Flora Tshinanu Musuamba
Journal:  Eur J Clin Pharmacol       Date:  2013-04-16       Impact factor: 2.953

6.  Practical management of boceprevir and immunosuppressive therapy in liver transplant recipients with hepatitis C virus recurrence.

Authors:  Audrey Coilly; Valérie Furlan; Bruno Roche; Caroline Barau; Coralie Noël; Laurence Bonhomme-Faivre; Teresa Maria Antonini; Anne-Marie Roque-Afonso; Didier Samuel; Anne-Marie Taburet; Jean-Charles Duclos-Vallée
Journal:  Antimicrob Agents Chemother       Date:  2012-08-20       Impact factor: 5.191

Review 7.  Population Pharmacokinetic Modelling and Bayesian Estimation of Tacrolimus Exposure: Is this Clinically Useful for Dosage Prediction Yet?

Authors:  Emily Brooks; Susan E Tett; Nicole M Isbel; Christine E Staatz
Journal:  Clin Pharmacokinet       Date:  2016-11       Impact factor: 6.447

8.  Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach.

Authors:  Tom M Nanga; Thao T P Doan; Pierre Marquet; Flora T Musuamba
Journal:  Br J Clin Pharmacol       Date:  2019-12-17       Impact factor: 4.335

9.  Evaluating tacrolimus pharmacokinetic models in adult renal transplant recipients with different CYP3A5 genotypes.

Authors:  Can Hu; Wen-Jun Yin; Dai-Yang Li; Jun-Jie Ding; Ling-Yun Zhou; Jiang-Lin Wang; Rong-Rong Ma; Kun Liu; Ge Zhou; Xiao-Cong Zuo
Journal:  Eur J Clin Pharmacol       Date:  2018-07-17       Impact factor: 2.953

10.  Multidrug resistance-associated protein 2 (MRP2/ABCC2) haplotypes significantly affect the pharmacokinetics of tacrolimus in kidney transplant recipients.

Authors:  Ken Ogasawara; Shripad D Chitnis; Reginald Y Gohh; Uwe Christians; Fatemeh Akhlaghi
Journal:  Clin Pharmacokinet       Date:  2013-09       Impact factor: 6.447

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