Limited-sampling strategies for anidulafungin in critically ill patients

Autor: Donald R. A. Uges, Marjolijn J. P. van Wanrooy, Michael G. G. Rodgers, Jos G. W. Kosterink, Tjip S. van der Werf, Johannes H. Proost, Jan G. Zijlstra, Jan-Willem C. Alffenaar
Přispěvatelé: Nanomedicine & Drug Targeting, Biopharmaceuticals, Discovery, Design and Delivery (BDDD), Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE)
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Bayes theorem
loading drug dose
NCT01047267
Bayes' theorem
Echinocandins
Statistics
Pharmacology (medical)
Prospective Studies
population model
drug monitoring
education.field_of_study
clinical article
medicine.diagnostic_test
adult
Area under the curve
article
Middle Aged
invasive candidiasis
aged
Infectious Diseases
female
priority journal
blood sampling
pharmacokinetics
medicine.drug
drug dose increase
medicine.medical_specialty
drug exposure
area under the curve
Critical Illness
Population
Clinical Therapeutics
minimum inhibitory concentration
anidulafungin
drug clearance
Young Adult
critically ill patient
Pharmacokinetics
male
Linear regression
medicine
Humans
Candidiasis
Invasive

controlled study
human
Intensive care medicine
education
Pharmacology
controlled clinical trial
business.industry
maximum plasma concentration
prediction
compartment model
minimum plasma concentration
Therapeutic drug monitoring
drug blood level
linear regression analysis
Anidulafungin
business
plasma concentration-time curve
Blood sampling
Zdroj: Antimicrobial Agents and Chemotherapy, 59(2), 1177-1181. AMER SOC MICROBIOLOGY
ISSN: 1098-6596
Popis: Efficacy of anidulafungin is driven by the area under the concentration-time curve (AUC)/MIC ratio. Determination of the anidulafungin AUC along with MIC values can therefore be useful. Since obtaining a full concentration-time curve to determine an AUC is not always feasible or appropriate, limited-sampling strategies may be useful in adequately estimating exposure. The objective of this study was to develop a model to predict the individual anidulafungin exposure in critically ill patients using limited-sampling strategies. Pharmacokinetic data were derived from 20 critically ill patients with invasive candidiasis treated with anidulafungin. These data were used to develop a two-compartment model in MW\Pharm using an iterative 2-stage Bayesian procedure. Limited-sampling strategies were subsequently investigated using two methods, a Bayesian analysis and a linear regression analysis. The best possible strategies for these two methods were evaluated by a Bland-Altman analysis for correlation of the predicted and observed AUC from 0 to 24 h (AUC 0–24 ) values. Anidulafungin exposure can be adequately estimated with the concentration from a single sample drawn 12 h after the start of the infusion either by linear regression ( R 2 = 0.99; bias, 0.05%; root mean square error [RMSE], 3%) or using a population pharmacokinetic model ( R 2 = 0.89; bias, −0.1%; RMSE, 9%) in critically ill patients and also in less severely ill patients, as reflected by healthy volunteers. Limited sampling can be advantageous for future studies evaluating the pharmacokinetics and pharmacodynamics of anidulafungin and for therapeutic drug monitoring in selected patients. (This study has been registered at ClinicalTrials.gov under registration no. NCT01047267.)
Databáze: OpenAIRE