Evidence map›Paper›PMID 22624503›Full record

ArticleClinical pharmacokinetics2012

Population pharmacokinetics and pharmacogenetics of everolimus in renal transplant patients.

Dirk Jan A R Moes, Rogier R Press, Jan den Hartigh, Tahar van der Straaten, Johan W de Fijter, Henk-Jan Guchelaar

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Article in Clinical pharmacokinetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
4.3field-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

36 citing papers in PubMed, 79 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Dirk Jan A R MoesDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Center, the Netherlands.
Rogier R Press
Jan den Hartigh
Tahar van der Straaten
Johan W de Fijter
Henk-Jan Guchelaar
Leiden University Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveEverolimus is a novel macrolide immunosuppressant used in the prevention of acute and chronic rejection of solid organ transplants. Everolimus is being actively investigated worldwide as a non-nephrotoxic alternative for calcineurin inhibitors. Its highly variable pharmacokinetics and narrow therapeutic window make it difficult to maintain an adequate exposure to prevent serious adverse effects. The primary objective of this study was to improve prediction of everolimus systemic exposure in renal transplant patients by describing the pharmacokinetics of everolimus and identifying the influence of demographic factors and a selection of polymorphisms in genes coding for ABCB1, CYP3A5, CYP2C8 and PXR. The secondary objective of this study was to develop a limited sampling strategy to enable prediction of everolimus exposure in an efficient way and to compare it with the widely used trough blood concentration (C(trough)) monitoring.

methodsA total of 783 blood samples were obtained from 53 renal transplant patients who had been switched from a triple therapy of ciclosporin, mycophenolate mofetil and prednisolone to a calcineurin inhibitor-free dual therapy of everolimus (twice daily) and prednisolone. Everolimus blood concentrations were analysed in whole blood using liquid chromatography-tandem mass spectrometry during routine therapeutic drug monitoring targeting an area under the blood concentration-time curve from time zero to 12 hours (AUC(12)) of 120 μg · h/L. A population pharmacokinetic model was developed and demographic factors and genetic polymorphisms in genes coding for ABCB1, CYP3A5, CYP2C8 and PXR were included as covariates. In addition, a limited sampling strategy was developed.

resultsMaintaining everolimus systemic exposure at an AUC(12) of 120 μg · h/L resulted in low rejection rates but considerable numbers of adverse events and toxicity. Everolimus pharmacokinetics were best described by a two-compartment model with lag-time (oral clearance = 17.9 L/h; volume of distribution of the central compartment after oral administration [V(1)/F] = 148 L and first-order absorption rate constant [k(a)] = 7.36 h-1). Ideal body weight was significantly related to V(1)/F. None of the selected polymorphisms in genes coding for enzymes involved in distribution and metabolism of everolimus had a significant influence on everolimus pharmacokinetics. The pharmacokinetic limited sampling model (C(trough) and whole blood drug concentration at 2 hours postdose [C(2)]) resulted in a significantly improved prediction of everolimus exposure compared with the widely used C(trough) monitoring.

conclusionA two-compartment pharmacokinetic model with lag-time describing the concentration-time profile of oral everolimus in renal transplant patients has been developed using pharmacokinetic modelling. Ideal body weight significantly influenced V(1)/F of everolimus; however, the selected polymorphisms in genes coding for ABCB1, CYP3A5, CYP2C8 and PXR had no clinically relevant effect on everolimus pharmacokinetics. Everolimus C(trough) and C(2) as a limited sampling model can be used to accurately estimate everolimus systemic exposure, an improvement over the widely used C(trough) monitoring.

Indexed as

Kidney TransplantationAdultAgedAryl Hydrocarbon HydroxylasesATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1Cytochrome P-450 CYP2C8Cytochrome P-450 CYP3AEverolimusFemaleHumansImmunosuppressive AgentsMaleMiddle AgedModels, BiologicalPolymorphism, GeneticABCB1 protein, humanAryl Hydrocarbon HydroxylasesATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1CYP2C8 protein, humanCYP3A5 protein, humanCytochrome P-450 CYP2C8Cytochrome P-450 CYP3AEverolimusImmunosuppressive AgentsPregnane X ReceptorReceptors, SteroidSirolimus

Identifiers

PMID22624503
OpenAlexW2087679865

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.