Evaluation of Limited Sampling Strategies for Bayesian Estimation of Daptomycin Area Under the Concentration-Time Curve: A Short Communication.


Journal

Therapeutic drug monitoring
ISSN: 1536-3694
Titre abrégé: Ther Drug Monit
Pays: United States
ID NLM: 7909660

Informations de publication

Date de publication:
01 08 2023
Historique:
received: 23 08 2022
accepted: 08 10 2022
medline: 13 7 2023
pubmed: 3 2 2023
entrez: 2 2 2023
Statut: ppublish

Résumé

Increasing evidence supports daptomycin therapeutic drug monitoring. The author's reference center used to perform therapeutic drug monitoring in patients who receive high-dose daptomycin for bone and joint infections, with a three-sample strategy to estimate the daptomycin daily area under the concentration-time curve (AUC). The objective of this study was to evaluate simpler strategies based on only 2 or 1 sample(s). The authors used the BestDose software to estimate the daptomycin AUC after Bayesian posterior estimation of individual pharmacokinetic (PK) parameters at steady state. The reference AUC (AUC full ) was based on 3 samples obtained predose (T0) and approximately 1 hour (T1) and 6 hours (T6) after the start of a 30-minute infusion of IV daptomycin. It was compared with the AUC based on all possible 2-sample and 1-sample strategies. Bias, imprecision, regression, and Bland-Altman plots were used to assess the performance of the alternative strategies. Data from 77 patients were analyzed. The mean AUC full value was 936 ± 373 mg·h/L. The best 2-sample strategy was T0 + T6, with a mean prediction bias of 0.13 mg·h/L and absolute imprecision of 3%. The T0 + T1 strategy also performed well with a mean bias of -10 mg·h/L and imprecision of 3%. The best 1-sample strategy was the T6 sample only with a bias of 2.19 mg·h/L and imprecision of 6%. Bayesian estimation of daptomycin AUC based on a two-sample strategy was associated with negligible bias and imprecision compared with the author's usual three-sample strategy. The trough and peak strategy may shorten and simplify patient visits and reduce assay labor and costs.

Identifiants

pubmed: 36728573
doi: 10.1097/FTD.0000000000001070
pii: 00007691-202308000-00014
doi:

Substances chimiques

Daptomycin NWQ5N31VKK

Banques de données

ClinicalTrials.gov
['NCT03134521']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

562-565

Informations de copyright

Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

Références

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Auteurs

Vianney Tuloup (V)

Hospices Civils de Lyon, Groupement Hospitalier Nord, Service de Pharmacie, Lyon.
Univ Lyon, Université Claude Bernard Lyon 1, Laboratoire de Biométrie et Biologie Évolutive Villeurbanne.

Aurélien Millet (A)

Hospices Civils de Lyon, Groupement Hospitalier Sud, Service de Biochimie et Biologie Moléculaire, UM Pharmacologie-Toxicologie, Lyon.

Alessandra Taricco (A)

Hospices Civils de Lyon, Groupement Hospitalier Nord, Service de Pharmacie, Lyon.

François Parant (F)

Hospices Civils de Lyon, Groupement Hospitalier Sud, Service de Biochimie et Biologie Moléculaire, UM Pharmacologie-Toxicologie, Lyon.

Tristan Ferry (T)

Hospices Civils de Lyon, Groupement Hospitalier Nord, Hôpital de la Croix-Rousse, Service des Maladies Infectieuses et Tropicales, Centre interrégional de Référence pour la prise en charge des Infections Ostéo-Articulaires complexes (CRIOAc Lyon), Lyon.
Univ Lyon, Université Lyon 1, ISPB, Facultés de Médecine et de Pharmacie de Lyon, Lyon, France; and.
CIRI-Centre International de Recherche en Infectiologie, Université́, Lyon, France.

Sylvain Goutelle (S)

Hospices Civils de Lyon, Groupement Hospitalier Nord, Service de Pharmacie, Lyon.
Univ Lyon, Université Claude Bernard Lyon 1, Laboratoire de Biométrie et Biologie Évolutive Villeurbanne.
Univ Lyon, Université Lyon 1, ISPB, Facultés de Médecine et de Pharmacie de Lyon, Lyon, France; and.

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