Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/175111
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dc.contributor.authorAndrews, L. M.-
dc.contributor.authorHesselink, D. A.-
dc.contributor.authorSchaik, R. H. N.-
dc.contributor.authorGelder, T.-
dc.contributor.authorFijter, J. W.-
dc.contributor.authorLloberas Blanch, Núria-
dc.contributor.authorElens, L.-
dc.contributor.authorMoes, D. J. A. R.-
dc.contributor.authorWinter, B. C. M.-
dc.date.accessioned2021-03-15T12:28:42Z-
dc.date.available2021-03-15T12:28:42Z-
dc.date.issued2019-01-17-
dc.identifier.urihttp://hdl.handle.net/2445/175111-
dc.description.abstractAims: The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient. Methods: Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed-effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. Results: A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two-compartment model. The mean absorption rate was 3.6 h-1 , clearance was 23.0 l h-1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: [Formula: see text] Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model. Conclusions: For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.-
dc.format.extent15 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherWiley-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1111/bcp.13838-
dc.relation.ispartofBritish Journal of Clinical Pharmacology, 2019, vol. 85, num. 3, p. 601-615-
dc.relation.urihttps://doi.org/10.1111/bcp.13838-
dc.rightscc by-nc (c) Andrews, L. M. et al., 2019-
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/*
dc.sourceArticles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))-
dc.subject.classificationFarmacocinètica-
dc.subject.classificationTrasplantament renal-
dc.subject.classificationImmunologia-
dc.subject.otherPharmacokinetics-
dc.subject.otherKidney transplantation-
dc.subject.otherImmunology-
dc.titleA population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients-
dc.typeinfo:eu-repo/semantics/article-
dc.date.updated2021-03-09T13:43:12Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.pmid30552703-
Appears in Collections:Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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