Limited sampling strategies for tacrolimus exposure (AUC(0-24)) predictionafter Prograf (R) and Advagraf (R) administration in children and adolescents with liver or kidney transplants

作者:Almeida Paulo Gonzalo N*; Lubomirov Rubin; Laura Alonso Sanchez Nazareth; Espinosa Roman Laura; Fernandez Camblor Carlota; Diaz Carmen; Munoz Bartola Gema; Carcas Sansuan Antonio J
来源:Transplant International, 2014, 27(9): 939-948.
DOI:10.1111/tri.12362

摘要

To develop limited sampling strategies (LSSs) to predict total tacrolimus exposure (AUC(0-24)) after the administration of Advagraf (R) and Prograf (R) (Astellas Pharma S. A, Madrid, Spain) to pediatric patients with stable liver or kidney transplants. Forty-one pharmacokinetic profiles were obtained after Prograf (R) and Advagraf (R) administration. LSSs predicting AUC(0-24) 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 AUC(0-24) than the correlation found between C-0 and AUC(0-24). Best LSS for Prograf (R) in liver transplants was C-0_1.5_4 (r(2) = 0.939) and for kidney transplants C-0_1_3 (r(2) = 0.925). For Advagraf (R), the best LSS in liver transplants was C-0_1_2.5 (r(2) = 0.938) and for kidney transplants was C-0_0.5_4 (r(2) = 0.931). Excluding transplant type variable, the best LSS for Prograf (R) is C0-1-3 (r(2) = 0.920) and the best LSS for Advagraf (R) was C-0_0.5_4 (r(2) = 0.926). Considering transplant type irrespective of the formulation used, the best LSS for liver transplants was C-0_2_3 (r(2) = 0.913) and for kidney transplants was C-0_0.5_4 (r(2) = 0.898). Best LSS, considering all data together, was C-0_1_4 (r(2) = 0.898). We developed several LSSs to predict AUC(0-24) for tacrolimus in children and adolescents with kidney or liver transplants after Prograf (R) and/or Advagraf (R) treatment.

  • 出版日期2014-9