Bayesian estimation of tobramycin exposure in cystic fibrosis

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

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Author Barras, Michael A.
Serisier, David
Hennig, Stefanie
Jess, Katrina
Norris, Ross L. G.
Title Bayesian estimation of tobramycin exposure in cystic fibrosis
Journal name Antimicrobial Agents and Chemotherapy   Check publisher's open access policy
ISSN 0066-4804
1098-6596
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
Language eng
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 (AUC(1)); and (iii) a Bayesian estimate using two concentrations (AUC(2)). 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 center dot h in each case, i.e., -8.2 (LLR), 3.8 (AUC(1)), and 1.0 (AUC(2)). 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.
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.
Keyword Microbiology
Pharmacology & Pharmacy
Microbiology
Pharmacology & Pharmacy
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Pharmacy Publications
 
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Created: Wed, 26 Oct 2016, 02:46:18 EST by Dr Stefanie Hennig on behalf of School of Pharmacy