title: Tacrolimus dose individualization in "de novo" patients after 10 years of experience in liver transplantation: pharmacokinetic considerations and patient pathophysiology.
abstract: OBJECTIVE
  To determine how changes in tacrolimus (TAC) immunosuppression clinical practice, in the first 15 days post liver transplantation (LT) and across a decade, impact a clinical covariate - pharmacokinetic (PK) model, developed in data from 1998, thus testing its utility in dose individualization across time. Patient cohorts from 1998 (Reference: R-1998) and 2007 (EVALUATION: E-2007) were compared.
  
  
  METHODS
  Analysis of monitoring observations (Cmin and Cmin/dose) and the biochemical variables aspartate aminotransferase (AST), hematocrit (HCT), albumin (ALB) and serum creatinine (SCr) was done for 0 - 3 and 4 - 15 days post transplantation (PT). The population PK model developed for R-1998 [1] was re-evaluated for the two cohorts.
  
  
  RESULTS
  Significant differences in R-1998 vs. E-2007 existed in Cmin and Cmin/dose and in covariates AST (as hepatic function marker) and SCr (as toxicity marker). E-2007 had lower levels of Cmin and Cmin/dose (1/CL), lower AST with faster recovery and lower variability in Cmin/dose for similar dose. AST was a covariate on CL/F in the 0 - 3 day PT period. In 4 - 15 days PT for E-2007, low levels of HCT and ALB as CL/F predictors confirmed a subgroup with higher CL/F (23.8 l/h vs. 19.3 l/h). The R-1998 model's original structure was confirmed.
  
  
  CONCLUSIONS
  Ten years of use of TAC shows gain in therapeutic targeting efficiency, due to improvement in LT methods, knowledge of the drug and consideration of PK steady state. The remaining uncertainty with TAC monitoring in LT can be resolved with application of PK principles combined with patients' diosyncrasies in the model developed for TAC dose individualization in R-1998. The applicability of the model as nucleus in Bayes individualization remains intact across a decade.
authors.affiliation: Department of Pharmacology, School of Medicine, University of the Basque Country, Bizkaia, Spain.
authors.forename: Naiara
authors.initials: N
authors.lastname: Valdivieso
authors.forename: Itziar
authors.initials: I
authors.lastname: Oteo
authors.forename: Andres
authors.initials: A
authors.lastname: Valdivieso
authors.forename: John C
authors.initials: JC
authors.lastname: Lukas
authors.forename: Nerea
authors.initials: N
authors.lastname: Leal
authors.forename: Mikel
authors.initials: M
authors.lastname: Gastaca
authors.forename: Jorge Ortiz
authors.initials: JO
authors.lastname: de Urbina
authors.forename: Rosario
authors.initials: R
authors.lastname: Calvo
authors.forename: Elena
authors.initials: E
authors.lastname: Suarez
mesh_terms: D001219:Aspartate Aminotransferases / Q000097:blood; D001499:Bayes Theorem; D015415:Biomarkers / Q000097:blood; D003404:Creatinine / Q000097:blood; D054796:Drug Dosage Calculations; D016903:Drug Monitoring; D006400:Hematocrit; D006801:Humans; D007166:Immunosuppressive Agents / Q000008:administration & dosage* / Q000009:adverse effects / Q000097:blood / Q000493:pharmacokinetics*; D016014:Linear Models; D016031:Liver Transplantation / Q000009:adverse effects / Q000276:immunology*; D008954:Models, Biological; D015233:Models, Statistical; D010818:Practice Patterns, Physicians' / Q000639:trends*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012709:Serum Albumin / Q000378:metabolism; D000075462:Serum Albumin, Human; D016559:Tacrolimus / Q000008:administration & dosage* / Q000009:adverse effects / Q000097:blood / Q000493:pharmacokinetics*
chemical_list: C422455:ALB protein, human; D015415:Biomarkers; D007166:Immunosuppressive Agents; D012709:Serum Albumin; D003404:Creatinine; D001219:Aspartate Aminotransferases; D016559:Tacrolimus; D000075462:Serum Albumin, Human