Trial reportBritish journal of clinical pharmacology2013
A published pharmacogenetic algorithm was poorly predictive of tacrolimus clearance in an independent cohort of renal transplant recipients.
Trial report in British journal of clinical pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 40 citations in OpenAlex.
- Associations between the gut microbiota and the metabolism rate of tacrolimus in kidney transplant recipients during the early posttransplant period.Archives of pharmacal research · 2025Observational
- Calcineurin inhibition may prevent Alzheimer disease in people with Down syndrome.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Synergistic Effect of Cytochrome P450 Family 3 Subfamily A Member 5 (ACS pharmacology & translational science · 2024Article
- A systematic review and meta-analysis recite the efficacy of Tacrolimus treatment in renal transplant patients in association with genetic variants ofAmerican journal of clinical and experimental urology · 2023Review
- Tacrolimus-why pharmacokinetics matter in the clinic.Frontiers in transplantation · 2023Review
- Current status of xenotransplantation research and the strategies for preventing xenograft rejection.Frontiers in immunology · 2022Review
- The Relationship between Initial Tacrolimus Metabolism Rate and Recipients Body Composition in Kidney Transplantation.Journal of clinical medicine · 2021Article
- Avoiding Tacrolimus Underexposure and Overexposure with a Dosing Algorithm for Renal Transplant Recipients: A Single Arm Prospective Intervention Trial.Clinical pharmacology and therapeutics · 2021Article
- Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients.Frontiers in pharmacology · 2021Article
- Fast Tac Metabolizers at Risk ⁻ It is Time for a C/D Ratio Calculation.Journal of clinical medicine · 2019Article
- A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients.British journal of clinical pharmacology · 2019Article
- Biomarkers and Pharmacogenomics in Kidney Transplantation.Molecular diagnosis & therapy · 2018Review
- Pharmacokinetics, Pharmacodynamics and Pharmacogenetics of Tacrolimus in Kidney Transplantation.Current drug metabolism · 2018Review
- CYP3A5 polymorphisms in renal transplant recipients: influence on tacrolimus treatment.Pharmacogenomics and personalized medicine · 2018Review
- Multigene predictors of tacrolimus exposure in kidney transplant recipients.Pharmacogenomics · 2015Article
- Article
- Role of pharmacogenomics in dialysis and transplantation.Current opinion in nephrology and hypertension · 2014Article
- Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling.British journal of clinical pharmacology · 2014Article
- Clinical implementation of pharmacogenetics in kidney transplantation: calcineurin inhibitors in the starting blocks.British journal of clinical pharmacology · 2014Review
- The role of pharmacogenetics in the disposition of and response to tacrolimus in solid organ transplantation.Clinical pharmacokinetics · 2014Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsAn algorithm based on the CYP3A5 genotype to predict tacrolimus clearance to inform the optimal initial dose was derived using data from the DeKAF study (Passey et al. Br J Clin Pharmacol 2011; 72: 948-57) but was not tested in an independent cohort of patients. Our aim was to test whether the DeKAF dosing algorithm could predict estimated tacrolimus clearance in renal transplant recipients at our centre.
methodsPredicted tacrolimus clearance based on the DeKAF algorithm was compared with dose-normalized trough whole-blood concentrations (estimated clearance) on day 7 after transplantation in a single-centre cohort of 255 renal transplant recipients.
resultsThere was a weak correlation (r = 0.431) between clearance based on dose-normalized trough whole-blood concentrations and DeKAF algorithm-predicted clearance. The means of the tacrolimus clearance predicted by the DeKAF algorithm and the estimated tacrolimus clearance based on the dose-normalized trough blood concentrations were plotted against the differences in the clearance as a Bland-Altman plot. Logarithmic transformation was performed owing to the increased difference in tacrolimus clearance as the mean clearance increased. There was a highly significant systematic error (P < 0.0005) characterized by a sloped regression line [gradient, 0.88 (95% confidence interval, 0.75-1.01)] on the Bland-Altman plot.
conclusionsThe DeKAF algorithm was unable to predict the estimated tacrolimus clearance accurately based on real tacrolimus doses and blood concentrations in our cohort of patients. Other genes are known to influence the clearance of tacrolimus, and a polygenic algorithm may be more predictive than those based on a single genotype.
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