ArticleEuropean journal of clinical pharmacology2018
Evaluating tacrolimus pharmacokinetic models in adult renal transplant recipients with different CYP3A5 genotypes.
Article in European journal of clinical pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Accelerating tacrolimus model-informed precision dosing in kidney transplant recipients: Model evaluation and refinement strategies.British journal of clinical pharmacology · 2026Pooled it
- Population Pharmacokinetic Models of Tacrolimus in Adult Transplant Recipients: A Systematic Review.Clinical pharmacokinetics · 2020Pooled it
- A Review of Population Pharmacokinetic Models and Dosing Algorithms Assessing the Influence of CYP3A5 Genotype and Other Clinical Covariates on Tacrolimus Pharmacokinetics.Clinical pharmacokinetics · 2026Review
- The Impact of CYP3A5 Genotype on Tacrolimus Pharmacokinetics in Children following Heart Transplant.Research square · 2026Article
- Article
- External assessment and refinement of a population pharmacokinetic model to guide tacrolimus dosing in pediatric heart transplant.Pharmacotherapy · 2023Article
- External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps.Clinical pharmacokinetics · 2023Article
- Predictive Performance of Published Tacrolimus Population Pharmacokinetic Models in Thai Kidney Transplant Patients.European journal of drug metabolism and pharmacokinetics · 2022Article
- Impact of Tacrolimus Daily Dose Limitation in Renal Transplant Recipients Expressing CYP3A5: A Retrospective Study.Journal of personalized medicine · 2021Article
- Precision Medicine in Kidney Transplantation: Just Hype or a Realistic Hope?Transplantation direct · 2021Article
- Comparison of the Predictive Performance Between Cystatin C and Serum Creatinine by Vancomycin via a Population Pharmacokinetic Models: A Prospective Study in a Chinese Population.European journal of drug metabolism and pharmacokinetics · 2020Article
- Tacrolimus troughs and genetic determinants of metabolism in kidney transplant recipients: A comparison of four ancestry groups.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2019Observational
- Population Pharmacokinetic Analysis of Immediate-Release Oral Tacrolimus Co-administered with Mycophenolate Mofetil in Corticosteroid-Free Adult Kidney Transplant Recipients.European journal of drug metabolism and pharmacokinetics · 2019Article
- Molecular Modeling-ACS omega · 2019Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
purposeNumerous studies have been conducted on the population pharmacokinetics of tacrolimus in adult renal transplant recipients. It has been reported that the cytochrome P450 (CYP) 3A5 genotype is an important cause of variability in tacrolimus pharmacokinetics. However, the predictive performance of population pharmacokinetic (PK) models of tacrolimus should be evaluated prior to their implementation in clinical practice. The aim of the study reported here was to test the predictive performance of these published PK models of tacrolimus.
methodsA literature search of the PubMed and Web of Science databases ultimately led to the inclusion of eight one-compartment models in our analysis. We collected a total of 1715 trough concentrations from 174 patients. Predictive performance was assessed based on visual and numerical comparison bias and imprecision and by the use of simulation-based diagnostics and Bayesian forecasting.
resultsOf the eight one-compartment models assessed, seven showed better predictive performance in CYP3A5 extensive metabolizers in terms of bias and imprecision. Results of the simulation-based diagnostics also supported the findings. The model based on a Chinese population in 2013 (model 3) showed the best and most stable predictive performance in all the tests and was more informative in CYP3A5 extensive metabolizers. As expected, Bayesian forecasting improved model predictability. Diversity among models and between different CYP3A5 genotypes of the same model was also narrowed by Bayesian forecasting.
conclusionsBased on our results, we recommend using model 3 in CYP3A5 extensive metabolizers in clinical practice. All models had a poor predictive performance in CYP3A5 poor metabolizers, and they should be used with caution in this patient population. However, Bayesian forecasting improved the predictability and reduced differences, and thus the models could be applied in this latter patient population for the design of maintenance dose.
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