Bayesian estimation of tobramycin exposure in patients with cystic fibrosis

Barras, Michael A., Serlsler, David, Hennig, Stefanie, Jess, Katrina and Norris, Ross L. G. (2016) Bayesian estimation of tobramycin exposure in patients with cystic fibrosis. Antimicrobial Agents and Chemotherapy, 60 11: 6698-6702. doi:10.1128/AAC.01131-16

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Author Barras, Michael A.
Serlsler, David
Hennig, Stefanie
Jess, Katrina
Norris, Ross L. G.
Title Bayesian estimation of tobramycin exposure in patients with cystic fibrosis
Journal name Antimicrobial Agents and Chemotherapy   Check publisher's open access policy
ISSN 0066-4804
Publication date 2016-11-01
Year available 2016
Sub-type Article (original research)
DOI 10.1128/AAC.01131-16
Open Access Status File (Publisher version)
Volume 60
Issue 11
Start page 6698
End page 6702
Total pages 5
Place of publication Washington, DC United States
Publisher American Society for Microbiology
Collection year 2017
Language eng
Formatted abstract
Fixed tobramycin (mg/kg) dosing is often inappropriate in patients with cystic fibrosis (CF), as pharmacokinetics are highly variable. The area under the concentration-time curve (AUC) is an exposure metric suited to monitoring in this population. Bayesian strategies to estimate AUC have been available for over 20 years but are not standard practice in the clinical setting. To assess their suitability for use in clinical practice, three AUC estimation methods using limited sampling were compared to measured true exposure by using intensive sampling tobramycin data. Adults prescribed once daily intravenous tobramycin had eight concentrations taken over 24 h. An estimate of true exposure within one dosing interval was calculated using the trapezoidal method and compared to three alternate estimates determined using (i) a two-sample log-linear regression (LLR) method (local hospital practice); (ii) a Bayesian estimate using one concentration (AUC1); and (iii) a Bayesian estimate using two concentrations (AUC2). Each method was evaluated against the true measured exposure by a Bland-Altman analysis. Twelve patients with a median (range) age and weight of 25 (18 to 36) years and 66.5 (51 to 76) kg, respectively, were recruited. There was good agreement between the true exposure and the three alternate estimates of AUC, with a mean AUC bias of <10 mg/liter · h in each case, i.e., −8.2 (LLR), 3.8 (AUC1), and 1.0 (AUC2). Bayesian analysis-based and LLR estimation methods of tobramycin AUC are equivalent to true exposure estimation. All three methods may be suitable for use in the clinical setting; however, a one-sample Bayesian method may be most useful in ambulatory patients for which coordinating blood samples is difficult. Suitably powered, randomized clinical trials are required to assess patient outcomes.
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Document type: Journal Article
Sub-type: Article (original research)
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Created: Tue, 07 Mar 2017, 16:11:40 EST by Ms Felicity Lindberg on behalf of School of Pharmacy