Critical assessment of the revised guidelines for vancomycin therapeutic drug monitoring.

Area under curve (AUC) Drug monitoring humans Methicillin-resistant Staphylococcus aureus* Trough monitoring Vancomycin / therapeutic use

Journal

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
ISSN: 1950-6007
Titre abrégé: Biomed Pharmacother
Pays: France
ID NLM: 8213295

Informations de publication

Date de publication:
Nov 2022
Historique:
received: 05 07 2022
revised: 26 09 2022
accepted: 28 09 2022
entrez: 22 10 2022
pubmed: 23 10 2022
medline: 26 10 2022
Statut: ppublish

Résumé

The revised vancomycin guidelines recommend replacing trough-only with trough or peak/trough Bayesian and first-order equations monitoring, citing their better AUC predictions and poor AUC-trough R The primary aim is to compare the predictive performance of the AUC monitoring methods. Then, we investigate the impact of not adhering to trough sampling on the Bayesian-based predictions. Moreover, we report the nature of PopPK priors used in Bayesian programs to assess the applicability of the guideline recommendations. We calculated the predictive performance of the monitoring methods using a standard PopPK modeling and simulation approach. We thoroughly explored the prior PK models implemented in Bayesian programs. Predictive performances of the monitoring methods were comparable at steady-state relative to the number of samples. Contrary to the recommendation, Bayesian trough monitoring did not result in better predictive performances compared to using random levels. Very few programs implemented richly-sampled priors. All the monitoring methods can be, relatively, reliable at steady-state, if properly implemented. Although only Bayesian-based monitoring can be used pre-steady-state, its predictive performance can be modest. Trough-only monitoring is the simplest approach. Constraints regarding trough sampling times could be relaxed. The scarcity of richly-sampled Bayesian priors questions the applicability of the revised guidelines recommendation.

Sections du résumé

BACKGROUND BACKGROUND
The revised vancomycin guidelines recommend replacing trough-only with trough or peak/trough Bayesian and first-order equations monitoring, citing their better AUC predictions and poor AUC-trough R
OBJECTIVES OBJECTIVE
The primary aim is to compare the predictive performance of the AUC monitoring methods. Then, we investigate the impact of not adhering to trough sampling on the Bayesian-based predictions. Moreover, we report the nature of PopPK priors used in Bayesian programs to assess the applicability of the guideline recommendations.
METHODS METHODS
We calculated the predictive performance of the monitoring methods using a standard PopPK modeling and simulation approach. We thoroughly explored the prior PK models implemented in Bayesian programs.
RESULTS RESULTS
Predictive performances of the monitoring methods were comparable at steady-state relative to the number of samples. Contrary to the recommendation, Bayesian trough monitoring did not result in better predictive performances compared to using random levels. Very few programs implemented richly-sampled priors.
CONCLUSION CONCLUSIONS
All the monitoring methods can be, relatively, reliable at steady-state, if properly implemented. Although only Bayesian-based monitoring can be used pre-steady-state, its predictive performance can be modest. Trough-only monitoring is the simplest approach. Constraints regarding trough sampling times could be relaxed. The scarcity of richly-sampled Bayesian priors questions the applicability of the revised guidelines recommendation.

Identifiants

pubmed: 36271558
pii: S0753-3322(22)01166-0
doi: 10.1016/j.biopha.2022.113777
pii:
doi:

Substances chimiques

Vancomycin 6Q205EH1VU
Anti-Bacterial Agents 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

113777

Informations de copyright

Copyright © 2022. Published by Elsevier Masson SAS.

Déclaration de conflit d'intérêts

Conflict of interest statement None.

Auteurs

Abdullah Aljutayli (A)

Department of Pharmaceutics, Faculty of Pharmacy, Qassim University, Saudi Arabia; Faculty of Pharmacy, Université de Montréal, Montréal, Canada, Faculty of Pharmacy, Qassim University, Saudi Arabia. Electronic address: abdullah.aljutayli@umontreal.ca.

Daniel J G Thirion (DJG)

Faculty of Pharmacy, Université de Montréal, Montréal, Canada; Department of Pharmacy, McGill University Health Center, Montréal, Québec, Canada.

Fahima Nekka (F)

Faculty of Pharmacy, Université de Montréal, Montréal, Canada; Laboratoire de Pharmacométrie, Faculté de Pharmacie, Université de Montréal, Montréal, Québec, Canada; Centre de recherches mathématiques, Université de Montréal, Montréal, Québec, Canada.

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Classifications MeSH