Comparison of the area under the curve for vancomycin estimated using compartmental and noncompartmental methods in adult patients with normal renal function
Date
2019
Authors
Shingde, R.V.
Graham, G.G.
Reuter, S.E.
Carland, J.E.
Day, R.O.
Stocker, S.L.
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Journal article
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Therapeutic Drug Monitoring, 2019; 41(6):726-731
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Abstract
Background: Vancomycin pharmacokinetics are best described using a 2-compartment model. However, 1-compartment population models are commonly used as the basis for dose prediction software.Therefore, the validity of using a 1-compartment model to guide vancomycin drug dosing was examined
Methods: Published plasma concentration-time data from adult subjects (n = 30) with stable renal function administered a single intravenous infusion of vancomycin were extracted from previous studies. The vancomycin area under the curve (AUC0-N) was calculated for each subject using noncompartmental methods (AUCNCA) and by fitting 1- (AUC1CMT), 2- (AUC2CMT), and 3- (AUC3CMT)compartment infusion models. The optimal model fit was determined using the Akaike information criterion and visual inspection of the residual plots. The individual compartmental AUC0-N values from the 1- and 2-compartment models were compared with AUCNCA values using one-way repeated measures analysis of variance
Results: The mean (6SD) AUC estimates were similar for the different methods: AUCNCA 180 6 86 mg$h/L, AUC1CMT 167 679 mg$h/L, and AUC2CMT 183 6 88 mg$h/L. Despite the overlapping AUC values, AUC2CMT and AUCNCA were significantly greater than AUC1CMT (P , 0.05). The 3-compartment model was excluded from the analysis because of the failure to converge in some instances
Conclusions: Dose prediction software using a 1-compartmentmodel as the basis for Bayesian forecasting underestimates drug exposure (estimated as the AUC) by less than 10%. This is unlikely to be clinically significant with respect to dose adjustment.Therefore, a 1-compartment model may be sufficient to guide vancomycin dosing in adult patients with stable renal function.
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Copyright 2019 Wolters Kluwer Health