Literature DB >> 11236810

Covariate effects on the apparent clearance of tacrolimus in paediatric liver transplant patients undergoing conversion therapy.

M J García Sánchez1, C Manzanares, D Santos-Buelga, A Blázquez, J Manzanares, P Urruzuno, E Medina.   

Abstract

OBJECTIVE: To analyse the influence of covariates on the apparent clearance (CL) of tacrolimus in paediatric liver transplant recipients being converted from cyclosporin to tacrolimus.
DESIGN: Retrospective modelling study. PATIENTS AND PARTICIPANTS: 18 children, 13 girls and 5 boys, aged 4 months to 16 years (median 9.1 years) who required conversion to tacrolimus because of acute or chronic rejection or cyclosporin toxicity.
METHODS: 287 whole-blood tacrolimus concentrations from therapeutic drug monitoring were used to build a nonlinear mixed-effects population model (NONMEM program) for the apparent clearance of tacrolimus. Variables considered were age, total bodyweight (TBW), body surface area (BSA), time after initiation of treatment (T), gender, haematocrit (Hct), albumin (Alb), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (gammaGT), alkaline phosphatase (ALP), bilirubin (BIL), creatinine clearance (CL(CR)) and dosage of concomitant corticosteroids (EST).
RESULTS: TBW, T, BIL and ALT were the covariates that displayed a significant influence on CL according to the final regression model: CL (L/h) = 10.4(TBW/70)3/4 x e(-0.00032 T) x e(-0.057 BIL) x (1 - 0.079 ALT). With this model, the estimates of the coefficients of variation were 24.3% and 29.5% for interpatient variability in CL and residual variability, respectively.
CONCLUSIONS: The proposed model for tacrolimus CL can be applied for a priori dosage calculations, although the results should be used with caution because of the unexplained variability in the CL. We therefore recommended close monitoring of tacrolimus whole blood concentrations, especially within the first months of treatment. The best use of the model would be its application in dosage adjustment based on therapeutic drug monitoring and the Bayesian approach.

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Year:  2001        PMID: 11236810     DOI: 10.2165/00003088-200140010-00005

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


  26 in total

1.  Demographic considerations in tacrolimus pharmacokinetics.

Authors:  W E Fitzsimmons; I Bekersky; D Dressler; K Raye; E Hodosh; Q Mekki
Journal:  Transplant Proc       Date:  1998-06       Impact factor: 1.066

2.  A size standard for pharmacokinetics.

Authors:  N H Holford
Journal:  Clin Pharmacokinet       Date:  1996-05       Impact factor: 6.447

3.  A simple estimate of glomerular filtration rate in children derived from body length and plasma creatinine.

Authors:  G J Schwartz; G B Haycock; C M Edelmann; A Spitzer
Journal:  Pediatrics       Date:  1976-08       Impact factor: 7.124

Review 4.  Tacrolimus (FK506): the pros and cons of its use as an immunosuppressant in pediatric liver transplantation.

Authors:  K L Cox; D K Freese
Journal:  Clin Invest Med       Date:  1996-10       Impact factor: 0.825

5.  Geometric method for measuring body surface area: a height-weight formula validated in infants, children, and adults.

Authors:  G B Haycock; G J Schwartz; D H Wisotsky
Journal:  J Pediatr       Date:  1978-07       Impact factor: 4.406

Review 6.  Tacrolimus. A review of its pharmacology, and therapeutic potential in hepatic and renal transplantation.

Authors:  D H Peters; A Fitton; G L Plosker; D Faulds
Journal:  Drugs       Date:  1993-10       Impact factor: 9.546

7.  FK506 conversion therapy in pediatric liver transplantation.

Authors:  H Egawa; C O Esquivel; S K So; K Cox; W Concepcion; L Lawrence
Journal:  Transplantation       Date:  1994-04-27       Impact factor: 4.939

8.  Pharmacokinetics and pharmacodynamics of FK 506 in pediatric patients receiving living-related donor liver transplantations.

Authors:  M Yasuhara; T Hashida; M Toraguchi; Y Hashimoto; M Kimura; K Inui; R Hori; Y Inomata; K Tanaka; Y Yamaoka
Journal:  Transplant Proc       Date:  1995-02       Impact factor: 1.066

9.  Factors affecting the pharmacokinetics of tacrolimus in the first year after renal transplantation. European Tacrolimus Multicentre Renal Study Group.

Authors:  N A Undre; A Schäfer
Journal:  Transplant Proc       Date:  1998-06       Impact factor: 1.066

10.  Randomised trial comparing tacrolimus (FK506) and cyclosporin in prevention of liver allograft rejection. European FK506 Multicentre Liver Study Group.

Authors: 
Journal:  Lancet       Date:  1994-08-13       Impact factor: 79.321

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  15 in total

1.  Population pharmacokinetics of tacrolimus in whole blood and plasma in asian liver transplant patients.

Authors:  Wai Johnn Sam; Lai San Tham; Michael J Holmes; Marion Aw; Seng Hock Quak; Kang Hoe Lee; Seng Gee Lim; Krishnan Prabhakaran; Sui Yung Chan; Paul C Ho
Journal:  Clin Pharmacokinet       Date:  2006       Impact factor: 6.447

Review 2.  Immunosuppressive therapy for paediatric transplant patients: pharmacokinetic considerations.

Authors:  María del Mar Fernández De Gatta; Dolores Santos-Buelga; Alfonso Domínguez-Gil; María José García
Journal:  Clin Pharmacokinet       Date:  2002       Impact factor: 6.447

Review 3.  Off-label use of tacrolimus in children with glomerular disease: Effectiveness, safety and pharmacokinetics.

Authors:  Guo-Xiang Hao; Lin-Lin Song; Dong-Feng Zhang; Le-Qun Su; Evelyne Jacqz-Aigrain; Wei Zhao
Journal:  Br J Clin Pharmacol       Date:  2020-01-14       Impact factor: 4.335

Review 4.  Drug interactions with tacrolimus.

Authors:  Teun van Gelder
Journal:  Drug Saf       Date:  2002       Impact factor: 5.606

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

Review 6.  Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation.

Authors:  Christine E Staatz; Susan E Tett
Journal:  Clin Pharmacokinet       Date:  2004       Impact factor: 6.447

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.  Population pharmacokinetic modelling and design of a Bayesian estimator for therapeutic drug monitoring of tacrolimus in lung transplantation.

Authors:  Caroline Monchaud; Brenda C de Winter; Christiane Knoop; Marc Estenne; Martine Reynaud-Gaubert; Christophe Pison; Marc Stern; Romain Kessler; Romain Guillemain; Pierre Marquet; Annick Rousseau
Journal:  Clin Pharmacokinet       Date:  2012-03-01       Impact factor: 6.447

10.  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.

Authors:  Dirk R J Kuypers; Kathleen Claes; Pieter Evenepoel; Bart Maes; Willy Coosemans; Jacques Pirenne; Yves Vanrenterghem
Journal:  Clin Pharmacokinet       Date:  2004       Impact factor: 6.447

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