Evidence map›Paper›PMID 27138785›Full record

ArticleClinical pharmacokinetics2016

The Effect of Weight and CYP3A5 Genotype on the Population Pharmacokinetics of Tacrolimus in Stable Paediatric Renal Transplant Recipients.

Agnieszka A Prytuła, Karlien Cransberg, Antonia H M Bouts, Ron H N van Schaik, Huib de Jong, Saskia N de Wildt, Ron A A Mathôt

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In one paragraph

Article in Clinical pharmacokinetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

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  10. Population pharmacokinetic analysis of tacrolimus in Chinese cardiac transplant recipients.European journal of hospital pharmacy : science and practice · 2020
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  17. A new donors'Oncotarget · 2017
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 2 countries.

Agnieszka A PrytułaPaediatric Nephrology Department, University Hospital Ghent, De Pintelaan 185, 9000, Ghent, Belgium. Agnieszka.Prytula@uzgent.be.
Karlien CransbergPaediatric Nephrology Department, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.
Antonia H M BoutsPaediatric Nephrology Department, Emma Children's Hospital, Amsterdam, The Netherlands.
Ron H N van SchaikDepartment of Clinical Chemistry, Erasmus MC, Rotterdam, The Netherlands.
Huib de JongPaediatric Nephrology Department, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.
Saskia N de WildtIntensive Care and Department of Paediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.
Ron A A MathôtDepartment of Hospital Pharmacy-Clinical Pharmacology Unit, Academic Medical Center, Amsterdam, The Netherlands.
Erasmus MC - Sophia Children’s Hospital · NLAcademic Medical Center · NLEmma Kinderziekenhuis · NLErasmus University Rotterdam · NLGhent University Hospital · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study was to develop a population pharmacokinetic model of tacrolimus in paediatric patients at least 1 year after renal transplantation and simulate individualised dosage regimens. PATIENTS AND

methodsWe included 54 children with median age of 11.1 years (range 3.8-18.4 years) with 120 pharmacokinetic profiles performed over 2 to 4 h. The pharmacokinetic analysis was performed using the non-linear mixed-effects modelling software (NONMEM(®)). The impact of covariates including concomitant medications, age, the cytochrome P450 (CYP) CYP3A5*3 gene and the adenosine triphosphate binding cassette protein B1 (ABCB1) 3435 C→T gene polymorphism on tacrolimus pharmacokinetics was analysed. The final model was externally validated on an independent dataset and dosing regimens were simulated.

resultsA two-compartment model adequately described tacrolimus pharmacokinetics. Apparent oral clearance (CL/F) was associated with weight (allometric scaling) but not age. Children with lower weight and CYP3A5 expressers required higher weight-normalised tacrolimus doses. CL/F was inversely associated with haematocrit (P < 0.05) and γ-glutamyl transpeptidase (γGT) (P < 0.001) and was increased by 45 % in carriers of the CYP3A5*1 allele (P < 0.001). CL/F was not associated with concomitant medications. Dose simulations show that a daily tacrolimus dose of 0.2 mg/kg generates a pre-dose concentration (C 0) ranging from 5 to 10 µg/L depending on the weight and CYP3A5 polymorphism. The median area under the plasma concentration-time curve (AUC) corresponding with a tacrolimus C 0 of 4-8 µg/L was 97 h·µg/L (interquartile range 80-120).

conclusionsIn patients beyond the first year after transplantation, there is a cumulative effect of CYP3A5*1 polymorphism and weight on the tacrolimus C 0. Children with lower weight and carriers of the CYP3A5*1 allele have higher weight-normalised tacrolimus dose requirements.

Indexed as

Kidney TransplantationTransplant RecipientsAdolescentArea Under CurveATP Binding Cassette Transporter, Subfamily B, Member 1Body WeightChildChild, PreschoolCohort StudiesCytochrome P-450 CYP3AFemaleGenotypeHumansImmunosuppressive AgentsMaleMetabolic Clearance RateATP Binding Cassette Transporter, Subfamily B, Member 1Cytochrome P-450 CYP3AImmunosuppressive AgentsTacrolimus

Identifiers

PMID27138785
OpenAlexW2343004967

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.