Literature DB >> 15301578

Time-related clinical determinants of long-term tacrolimus pharmacokinetics in combination therapy with mycophenolic acid and corticosteroids: a prospective study in one hundred de novo renal transplant recipients.

Dirk R J Kuypers1, Kathleen Claes, Pieter Evenepoel, Bart Maes, Willy Coosemans, Jacques Pirenne, Yves Vanrenterghem.   

Abstract

BACKGROUND: Tacrolimus is an efficient primary immunosuppressive drug in renal transplantation but its long-term use is associated with calcineurin-inhibitor-related toxicity. The specific characteristics of the inter-relationship between dose, concentration and clinical (side-)effects for tacrolimus have not yet been identified and extensive long-term pharmacokinetic studies are presently lacking.
OBJECTIVE: To establish the characteristics of the long-term pharmacokinetics of tacrolimus, to determine the time-dependent factors that influence the pharmacokinetics within the first critical post-transplant year and to identify a more appropriate way of monitoring drug exposure in clinical practice. STUDY
DESIGN: A prospective pharmacokinetic study of tacrolimus was conducted in 100 de novo renal allograft recipients during the first year post-transplantation.
METHODS: Area under the concentration-time curve (AUC) blood samplings for tacrolimus were performed on days 7, 42, 90, 180 and 360 for all patients. Model-independent pharmacokinetic parameters for tacrolimus were calculated and dose-corrected when appropriate: AUC12, peak plasma concentration (Cmax), pre-dose trough concentration (C0), time to Cmax, average steady-state blood concentration, steady-state total body clearance, terminal half-life, volume of distribution and an estimate for tacrolimus bioavailability was derived from additional steady-state intravenous clearance data. The association between tacrolimus pharmacokinetic parameters and different clinical variables was evaluated on days 7, 42, 90, 180 and 360. The clinical variables were either donor-related (e.g. donor age), transplantation-related (e.g. delayed graft function), recipient-related (e.g. bodyweight), biochemical (e.g. serum albumin), therapeutic variables (e.g. corticosteroid dose) or disease variables (e.g. liver dysfunction).
RESULTS: Long-term tacrolimus dose-corrected exposure (AUC12, C0) is characterised by a late significant increase towards the end of the first year post-transplantation as the result of a significant increase in tacrolimus bioavailability (p < 0.05) and a slow decrease in tacrolimus steady-state clearance. Consequently, tacrolimus dose-requirements corrected for bodyweight decrease significantly in the first postoperative year (p < 0.05), in part because of the simultaneous tapering of the corticosteroid dose which significantly affects tacrolimus bioavailability (p < 0.05). Other clinical variables that significantly influenced tacrolimus administration, exposure and bioavailability in a time-related fashion were identified in this study (renal allograft function [p < 0.05], liver dysfunction [p < 0.05], diarrhoea [p < 0.05]), while the clinical relevance of other variables was considerably moderated by our findings (serum albumin, haematocrit). Time-unrelated variables proved to be of significant continuing clinical importance for tacrolimus dose-exposure pharmacokinetics throughout the first post-transplant year (recipient age [p < 0.05], gender [p < 0.01] and donor-receptor gender mismatch [p < 0.05]), while donor hypotension (p < 0.05) and cold ischaemia time (p < 0.05) also proved significant although at present the reasons for this are unknown. Finally, using multiple stepwise regression analysis we demonstrated that classical assessment of tacrolimus exposure by monitoring pre-dose trough blood concentration (or any other single concentration sampling timepoint) is not the most reliable method and that abbreviated AUC measurements may constitute a more accurate clinical tool for (therapeutic) monitoring of drug exposure.
CONCLUSION: Tacrolimus pharmacokinetics in the first year after renal transplantation are characterised by a specific time-dependent evolution. The identification of clinical variables that determine tacrolimus pharmacokinetics is an important aid in the development of reliable drug monitoring strategies using abbreviated AUC measurements.

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Year:  2004        PMID: 15301578     DOI: 10.2165/00003088-200443110-00005

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  66 in total

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Journal:  Transplant Proc       Date:  2002-06       Impact factor: 1.066

2.  Elevated tacrolimus trough levels in association with mycophenolate mofetil-induced diarrhea: a case report.

Authors:  M Frühwirth; H Fischer; B Simma; H Ellemunter
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5.  Tacrolimus clearance is age-dependent within the pediatric population.

Authors:  D Przepiorka; D Blamble; S Hilsenbeck; M Danielson; R Krance; K W Chan
Journal:  Bone Marrow Transplant       Date:  2000-09       Impact factor: 5.483

6.  Faster clearance of sustained release verapamil in men versus women: continuing observations on sex-specific differences after oral administration of verapamil.

Authors:  M E Krecic-Shepard; C R Barnas; J Slimko; J B Schwartz
Journal:  Clin Pharmacol Ther       Date:  2000-09       Impact factor: 6.875

7.  A comparison of tacrolimus (FK506) and cyclosporine for immunosuppression after cadaveric renal transplantation. FK506 Kidney Transplant Study Group.

Authors:  J D Pirsch; J Miller; M H Deierhoi; F Vincenti; R S Filo
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8.  A limited sampling strategy for the estimation of eight-hour neoral areas under the curve in renal transplantation.

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9.  Population pharmacokinetics of tacrolimus in adult kidney transplant recipients.

Authors:  Christine E Staatz; Charlene Willis; Paul J Taylor; Susan E Tett
Journal:  Clin Pharmacol Ther       Date:  2002-12       Impact factor: 6.875

Review 10.  Mechanisms of clinically relevant drug interactions associated with tacrolimus.

Authors:  Uwe Christians; Wolfgang Jacobsen; Leslie Z Benet; Alfonso Lampen
Journal:  Clin Pharmacokinet       Date:  2002       Impact factor: 6.447

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1.  Evaluation of limited sampling methods for estimation of tacrolimus exposure in adult kidney transplant recipients.

Authors:  Katherine A Barraclough; Nicole M Isbel; Carl M Kirkpatrick; Katie J Lee; Paul J Taylor; David W Johnson; Scott B Campbell; Diana R Leary; Christine E Staatz
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2.  The CYP3A biomarker 4β-hydroxycholesterol does not improve tacrolimus dose predictions early after kidney transplantation.

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3.  Donor CYP3A5 genotype influences tacrolimus disposition on the first day after paediatric liver transplantation.

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Review 4.  Review article: The pharmacokinetics and pharmacodynamics of drugs used in inflammatory bowel disease treatment.

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5.  Impact of the CYP3A5 genotype on the distributions of dose-adjusted trough concentrations and incidence of rejection in Japanese renal transplant recipients receiving different tacrolimus formulations.

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6.  Weight of ABCB1 and POR genes on oral tacrolimus exposure in CYP3A5 nonexpressor pediatric patients with stable kidney transplant.

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7.  Evaluation of limited sampling strategies for tacrolimus.

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Journal:  Eur J Clin Pharmacol       Date:  2007-08-22       Impact factor: 2.953

8.  Determination of the most influential sources of variability in tacrolimus trough blood concentrations in adult liver transplant recipients: a bottom-up approach.

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Review 9.  Population Pharmacokinetic Modelling and Bayesian Estimation of Tacrolimus Exposure: Is this Clinically Useful for Dosage Prediction Yet?

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Journal:  Clin Pharmacokinet       Date:  2016-11       Impact factor: 6.447

10.  Donor age and renal P-glycoprotein expression associate with chronic histological damage in renal allografts.

Authors:  Maarten Naesens; Evelyne Lerut; Hylke de Jonge; Boudewijn Van Damme; Yves Vanrenterghem; Dirk R J Kuypers
Journal:  J Am Soc Nephrol       Date:  2009-09-17       Impact factor: 10.121

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