Evidence map›Paper›PMID 39283469›Full record

ArticleEuropean journal of drug metabolism and pharmacokinetics2024

Vancomycin in Pediatric Patients with Cystic Fibrosis: Dose Optimization Using Population Pharmacokinetic Approach.

Aysenur Yaliniz, Mathieu Blouin, Marie-Élaine Métras, Marie-Christine Boulanger, Karine Cloutier, Marie-Hélène Dubé, Julie Autmizguine, Amélie Marsot

Abstract readMulticenter Study
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In one paragraph

Article in European journal of drug metabolism and pharmacokinetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Aysenur YalinizSTP2 Laboratory, Faculty of Pharmacy, Université de Montréal, 2940 Chemin de Polytechnique, Montreal, QC, H3T 1J4, Canada. aysenur.yaliniz@umontreal.ca.ORCID http://orcid.org/0009-0006-0447-7668
Mathieu BlouinSTP2 Laboratory, Faculty of Pharmacy, Université de Montréal, 2940 Chemin de Polytechnique, Montreal, QC, H3T 1J4, Canada.
Marie-Élaine MétrasFaculty of Pharmacy, Université de Montréal, Montreal, Canada.
Marie-Christine BoulangerFaculty of Pharmacy, Université Laval, Quebec, Canada.
Karine CloutierFaculty of Pharmacy, Université Laval, Quebec, Canada.
Marie-Hélène DubéFaculty of Pharmacy, Université Laval, Quebec, Canada.
Julie AutmizguineDepartment of Pharmacology, Faculty of Medicine, Université de Montréal, Montreal, Canada.
Amélie MarsotSTP2 Laboratory, Faculty of Pharmacy, Université de Montréal, 2940 Chemin de Polytechnique, Montreal, QC, H3T 1J4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn increase in Staphylococcus aureus infections has been reported in pediatric patients with cystic fibrosis (CF) over the last few years. This pathogen is commonly treated with vancomycin, an antibiotic for which therapeutic drug monitoring (TDM) is recommended. Updated guidelines were recently published regarding new targets of exposure for the TDM of vancomycin through a Bayesian approach, using population pharmacokinetic (popPK) models.

objectivesThis study aims to assess the predictive performance of vancomycin popPK models in pediatric patients with CF and to recommend optimal initial dosing regimens based on simulations.

methodsPatient data were collected from two centers in Canada, and a literature review was conducted to identify all published vancomycin popPK models for pediatric CF patients. External evaluation and simulations were performed according to patient and occasion of treatment.

resultsA total of 53 vancomycin concentrations were collected from six pediatric CF patients. Only two popPK models of vancomycin for pediatric CF patients were identified through the literature review. The external evaluation results for both centers combined revealed a population bias of 28.1% and an imprecision of 33.7%. A re-estimation of parameters was performed to improve predictive performance. The optimal initial dosing regimen was 15 mg/kg/dose administered every 6 hours according to the per occasion remodel.

conclusionThe predictive performance and identified optimal initial dosing regimens associated with the model were different depending on the data used, showing external evaluation's importance before implementing a model in clinical practice.

Indexed as

Anti-Bacterial AgentsCystic FibrosisDrug MonitoringModels, BiologicalVancomycinAdolescentBayes TheoremCanadaChildChild, PreschoolDose-Response Relationship, DrugFemaleHumansMaleStaphylococcal InfectionsAnti-Bacterial AgentsVancomycin

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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.