Modeling of Tacrolimus Exposure in Kidney Transplant According to Posttransplant Time Based on Routine Trough Concentration Data
| Autor: | Nadia, Ben Fredj, Jean Baptiste, Woillard, Jean, Debord, Amel, Chaabane, Naceur, Boughattas, Pierre, Marquet, Franck, Saint-Marcoux, Karim, Aouam |
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| Rok vydání: | 2016 |
| Předmět: |
Adult
Graft Rejection Male Tunisia Adolescent Metabolic Clearance Rate Calcineurin Inhibitors Graft Survival Reproducibility of Results Middle Aged Kidney Transplantation Models Biological Tacrolimus Young Adult Treatment Outcome Humans Female Drug Monitoring Child Immunosuppressive Agents Retrospective Studies |
| Zdroj: | Experimental and clinical transplantation : official journal of the Middle East Society for Organ Transplantation. 14(4) |
| ISSN: | 2146-8427 |
| Popis: | The aim of this study was to develop a pharmacokinetics model allowing the description of the evolution of tacrolimus exposure in kidney transplant patients over the first months after transplant, using trough concentrations of routinely collected blood.The authors performed a retrospective analysis of trough concentration data collected from adult kidney transplant recipients (from 2008 to 2013). The total data set was divided into a building data set, used to build the structural model, and a validation data set, used to validate the structural model. (C0 = 133; 26 patients). A pharmacokinetics analysis was carried out by applying a nonparametric adaptive grid approach. The structural model parameters were tacrolimus clearance and volume of distribution.In patients in the building set group, estimated clearance was 3.6 ± 0.57 L/h and estimated volume of distribution was 9.9 ± 1.14 L. No covariate was significantly associated with tacrolimus clearance or volume of distribution. The model adequately described tacrolimus dose-normalized trough concentration evolution after transplant (the plot of individual model predicted versus observed concentrations resulted in r = 0.84). The prediction performance in the validation group yielded 2.3% mean prediction error and 21.4% root mean squared error.This model could be highly useful in the optimization of tacrolimus prescription at any posttransplant time in kidney transplant patients. |
| Databáze: | OpenAIRE |
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