International journal of clinical pharmacology and therapeutics · 2024
Comparison of vancomycin area under the curve calculated based on Bayesian approach versus equation-based approach.
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Kim Tae Wan, Piao Jinghua, Bocchi Vittoria D, Koo So Yeon, Choi Se Joon, Chaudhry Fayzan, Yang Donghe, Cho Hyein S, Hergenreder Emiliano, Ruiz Perera Lucia, Joshi Subhashini, Abou Mrad Zaki, Claros Nidia, Donohue Shkurte Ademi, Eun Im Yeong, Jeong Hyo Jae, Frank Anika K, Walsh Ryan M, Mosharov Eugene V, Betel Doron, Tabar Viviane, Studer Lorenz
Аннотация
OBJECTIVE: Area under the curve (AUC)-based vancomycin dose adjustment is recommended to treat methicillin-resistant Staphylococcus aureus (MRSA) infections. AUC estimation methods include Bayesian software programs and simple analytical equations. This study compared the AUC obtained using the Bayesian approach with that obtained using an equation-based approach.
MATERIALS AND METHODS: Patients receiving intravenous vancomycin for MRSA infection were included. Peak and trough levels were measured for each patient on days 3, 7, and 10 post vancomycin dosing (day 1). AUC was calculated using software based on the Bayesian method (MwPharm Online) and an equation-based calculator, Stanford Health Care (SHC) calculator.
RESULTS: The AUC estimated using MwPharm Online was similar to that estimated using the SHC calculator. The geometric mean ratio (GMR) and their 90% confidence intervals (90% CI) were 1.08 (1.05 - 1.11), 1.03 (0.99 - 1.07), and 0.99 (0.94 - 1.05) at days 3, 7, and 10, respectively. Furthermore, according to the software used, there were no significant differences in the proportions of patients in the categories "within" and "below or above" the AUC target range. Additionally, trough levels predicted by both software programs were lower than the observed ones. Still, there was no significant difference between the predicted and observed peak levels for both software programs on day 10.
CONCLUSION: AUC calculated using the Bayesian software allows for calculation with samples at a non-steady state, can integrate covariates, and is interconvertible with that estimated using an equation-based calculator, which is simpler and relies on fewer assumptions. Therefore, either method can be used, considering each method's strengths and limitations.
MATERIALS AND METHODS: Patients receiving intravenous vancomycin for MRSA infection were included. Peak and trough levels were measured for each patient on days 3, 7, and 10 post vancomycin dosing (day 1). AUC was calculated using software based on the Bayesian method (MwPharm Online) and an equation-based calculator, Stanford Health Care (SHC) calculator.
RESULTS: The AUC estimated using MwPharm Online was similar to that estimated using the SHC calculator. The geometric mean ratio (GMR) and their 90% confidence intervals (90% CI) were 1.08 (1.05 - 1.11), 1.03 (0.99 - 1.07), and 0.99 (0.94 - 1.05) at days 3, 7, and 10, respectively. Furthermore, according to the software used, there were no significant differences in the proportions of patients in the categories "within" and "below or above" the AUC target range. Additionally, trough levels predicted by both software programs were lower than the observed ones. Still, there was no significant difference between the predicted and observed peak levels for both software programs on day 10.
CONCLUSION: AUC calculated using the Bayesian software allows for calculation with samples at a non-steady state, can integrate covariates, and is interconvertible with that estimated using an equation-based calculator, which is simpler and relies on fewer assumptions. Therefore, either method can be used, considering each method's strengths and limitations.