title: External evaluation of published population pharmacokinetic models of tacrolimus in adult renal transplant recipients.
abstract: OBJECTIVE
  Several tacrolimus population pharmacokinetic models in adult renal transplant recipients have been established to facilitate dose individualization. However, their applicability when extrapolated to other clinical centres is not clear. This study aimed to (1) evaluate model external predictability and (2) analyze potential influencing factors.
  
  
  METHODS
  Published models were screened from the literature and were evaluated using an external dataset with 52 patients (609 trough samples) collected by postoperative day 90 via methods that included (1) prediction-based prediction error (PE%), (2) simulation-based prediction- and variability-corrected visual predictive check (pvcVPC) and normalized prediction distribution error (NPDE) tests and (3) Bayesian forecasting to assess the influence of prior observations on model predictability. The factors influencing model predictability, particularly the impact of structural models, were evaluated.
  
  
  RESULTS
  Sixteen published models were evaluated. In prediction-based diagnostics, the PE% within ±30% was less than 50% in all models, indicating unsatisfactory predictability. In simulation-based diagnostics, both the pvcVPC and the NPDE indicated model misspecification. Bayesian forecasting improved model predictability significantly with prior 2-3 observations. The various factors influencing model extrapolation included bioassays, the covariates involved (CYP3A5*3 polymorphism, postoperative time and haematocrit) and whether non-linear kinetics were used.
  
  
  CONCLUSIONS
  The published models were unsatisfactory in prediction- and simulation-based diagnostics, thus inappropriate for direct extrapolation correspondingly. However Bayesian forecasting could improve the predictability considerably with priors. The incorporation of non-linear pharmacokinetics in modelling might be a promising approach to improving model predictability.
authors.affiliation: Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040.
authors.forename: Chen-Yan
authors.initials: CY
authors.lastname: Zhao
authors.affiliation: Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Jiao
authors.affiliation: Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040.|Department of Clinical Pharmacy, School of Pharmacy, Fudan University, 826 Zhang Heng Road, Shanghai, 201203, China.
authors.forename: Jun-Jun
authors.initials: JJ
authors.lastname: Mao
authors.affiliation: Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040.
authors.forename: Xiao-Yan
authors.initials: XY
authors.lastname: Qiu
mesh_terms: D019540:Area Under Curve; D001499:Bayes Theorem; D015331:Cohort Studies; D051544:Cytochrome P-450 CYP3A / Q000235:genetics; D006400:Hematocrit; D006801:Humans; D007166:Immunosuppressive Agents / Q000493:pharmacokinetics*; D016030:Kidney Transplantation; D008954:Models, Biological; D011110:Polymorphism, Genetic; D011184:Postoperative Period; D012189:Retrospective Studies; D016559:Tacrolimus / Q000493:pharmacokinetics*; D066027:Transplant Recipients
chemical_list: D007166:Immunosuppressive Agents; D051544:Cytochrome P-450 CYP3A; D016559:Tacrolimus
keywords: adult renal transplant recipients; external evaluation; non-linear kinetics; population pharmacokinetics; tacrolimus