Literature DB >> 24861353

Limited sampling strategies for tacrolimus exposure (AUC0-24) prediction after Prograf(®) and Advagraf(®) administration in children and adolescents with liver or kidney transplants.

Gonzalo N Almeida-Paulo1, Rubin Lubomirov, Nazareth Laura Alonso-Sanchez, Laura Espinosa-Román, Carlota Fernández Camblor, Carmen Díaz, Gema Muñoz Bartola, Antonio J Carcas-Sansuán.   

Abstract

To develop limited sampling strategies (LSSs) to predict total tacrolimus exposure (AUC0-24 ) after the administration of Advagraf(®) and Prograf(®) (Astellas Pharma S.A, Madrid, Spain) to pediatric patients with stable liver or kidney transplants. Forty-one pharmacokinetic profiles were obtained after Prograf(®) and Advagraf(®) administration. LSSs predicting AUC0-24 were developed by linear regression using three extraction time points. Selection of the most accurate LSS was made based on the r(2) , mean error, and mean absolute error. All selected LSSs had higher correlation with AUC0-24 than the correlation found between C0 and AUC0-24 . Best LSS for Prograf(®) in liver transplants was C0_1.5_4 (r(2)  = 0.939) and for kidney transplants C0_1_3 (r(2)  = 0.925). For Advagraf(®) , the best LSS in liver transplants was C0_1_2.5 (r(2)  = 0.938) and for kidney transplants was C0_0.5_4 (r(2)  = 0.931). Excluding transplant type variable, the best LSS for Prograf(®) is C0-1-3 (r(2)  = 0.920) and the best LSS for Advagraf(®) was C0_0.5_4 (r(2)  = 0.926). Considering transplant type irrespective of the formulation used, the best LSS for liver transplants was C0_2_3 (r(2)  = 0.913) and for kidney transplants was C0_0.5_4 (r(2)  = 0.898). Best LSS, considering all data together, was C0_1_4 (r(2)  = 0.898). We developed several LSSs to predict AUC0-24 for tacrolimus in children and adolescents with kidney or liver transplants after Prograf(®) and/or Advagraf(®) treatment.
© 2014 Steunstichting ESOT.

Entities:  

Keywords:  kidney; limited sampling strategies; liver; pediatric; tacrolimus; transplant

Mesh:

Substances:

Year:  2014        PMID: 24861353     DOI: 10.1111/tri.12362

Source DB:  PubMed          Journal:  Transpl Int        ISSN: 0934-0874            Impact factor:   3.782


  5 in total

1.  Population pharmacokinetic model and Bayesian estimator for 2 tacrolimus formulations in adult liver transplant patients.

Authors:  Camille Riff; Jean Debord; Caroline Monchaud; Pierre Marquet; Jean-Baptiste Woillard
Journal:  Br J Clin Pharmacol       Date:  2019-06-14       Impact factor: 4.335

2.  Limited sampling strategies for once daily tacrolimus exposure monitoring.

Authors:  Antonio J Carcas-Sansuán
Journal:  Eur J Clin Pharmacol       Date:  2016-03-03       Impact factor: 2.953

3.  Response: Limited sampling strategies for once daily tacrolimus exposure monitoring.

Authors:  D J A R Moes; J J Swen; S A S van der Bent; T van der Straaten; A Inderson; E Olofsen; H W Verspaget; H J Guchelaar; J den Hartigh; B van Hoek
Journal:  Eur J Clin Pharmacol       Date:  2016-03-02       Impact factor: 2.953

4.  Tacrolimus dose adjustment is not necessary in dose to dose conversion from a twice daily to a prolonged release once daily dose form.

Authors:  Kanitha Tiankanon; Stephen J Kerr; Siriwan Thongthip; Suwasin Udomkarnjananun; Pimpayao Sodsai; Athaya Vorasittha; Kamol Panumatrassamee; Kullaya Takkavatakarn; Kriang Tungsanga; Somchai Eiam-Ong; Kearkiat Praditpornsilpa; Yingyos Avihingsanon; Natavudh Townamchai
Journal:  Sci Rep       Date:  2022-06-16       Impact factor: 4.996

5.  Variations in Practice to Therapeutic Monitoring of Tacrolimus following Primary Adult Liver Transplantation.

Authors:  B V M Dasari; J Hodson; A Nassir; J Widmer; J Isaac; H Mergentel; P Muiesan; D F Mirza; M T P R Perera
Journal:  Int J Organ Transplant Med       Date:  2016-02-01
  5 in total

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