TY - JOUR
T1 - Comparison of Bayesian-derived and first-order analytic equations for calculation of vancomycin area under the curve
AU - Olney, Katie B.
AU - Wallace, Katie L.
AU - Mynatt, Ryan P.
AU - Burgess, David S.
AU - Grieves, Kaitlyn
AU - Willett, Austin
AU - Mani, Johann
AU - Flannery, Alexander H.
N1 - Publisher Copyright:
© 2022 Pharmacotherapy Publications, Inc.
PY - 2022/4
Y1 - 2022/4
N2 - Introduction: Consensus guidelines recommend targeting a vancomycin area under the curve to minimum inhibitory concentration (AUC24:MIC) ratio of 400–600 to improve therapeutic success and reduce nephrotoxicity. Although guidelines specify either Bayesian software or first-order equations may be used to estimate AUC24, there are currently no large studies directly comparing these methods. Objective: To compare calculated vancomycin AUC24 using first-order equations with two-drug concentrations at steady state to Bayesian two- and one-concentration estimations. Methods: This was a single-center, retrospective cohort study of 978 adult hospitalized patients receiving intravenous vancomycin between 2017 and 2019. Patients were included if they received at least 72 h of vancomycin and had two-serum drug concentrations obtained. AUC24 was calculated using first-order analytic (linear), Bayesian two-concentration, and Bayesian one-concentration methods for each patient. The InsightRx™ software platform was used to calculate Bayesian AUC24. Pearson's correlation and clinical agreement (based on AUC24 classified as subtherapeutic, therapeutic, or supratherapeutic) were used to assess agreement between methods. Bland–Altman plots were used to assess mean difference (MD) and 95% limits of agreement (LOA). Results: Excellent agreement was observed between linear and Bayesian two-concentration methods (r = 0.963, clinical agreement = 87.4%) and Bayesian two-concentration and one-concentration methods (r = 0.931, clinical agreement = 88.5%); however, a degree of variability was noted with 95% LOA −99 to 76 (MD = −11.5 mg*h/L) and −92 to 113 (MD = −10.4 mg*h/L), for the respective comparisons. The agreement between linear and Bayesian one-concentration approaches was less than prior comparisons (r = 0.823, clinical agreement = 76.8%) and demonstrated the greatest amount of variability with 95% LOA −197 to 153 (MD = −21.9 mg*h/L). Conclusions: Linear and Bayesian two-concentration methods demonstrated high-level agreement with acceptable variability and may be considered comparable to estimate vancomycin AUC24. As linear and Bayesian one-concentration methods demonstrated significant variability and suboptimal agreement, concerns exist surrounding the interchangeability of these methods in clinical practice, particularly at higher extremes of AUC24.
AB - Introduction: Consensus guidelines recommend targeting a vancomycin area under the curve to minimum inhibitory concentration (AUC24:MIC) ratio of 400–600 to improve therapeutic success and reduce nephrotoxicity. Although guidelines specify either Bayesian software or first-order equations may be used to estimate AUC24, there are currently no large studies directly comparing these methods. Objective: To compare calculated vancomycin AUC24 using first-order equations with two-drug concentrations at steady state to Bayesian two- and one-concentration estimations. Methods: This was a single-center, retrospective cohort study of 978 adult hospitalized patients receiving intravenous vancomycin between 2017 and 2019. Patients were included if they received at least 72 h of vancomycin and had two-serum drug concentrations obtained. AUC24 was calculated using first-order analytic (linear), Bayesian two-concentration, and Bayesian one-concentration methods for each patient. The InsightRx™ software platform was used to calculate Bayesian AUC24. Pearson's correlation and clinical agreement (based on AUC24 classified as subtherapeutic, therapeutic, or supratherapeutic) were used to assess agreement between methods. Bland–Altman plots were used to assess mean difference (MD) and 95% limits of agreement (LOA). Results: Excellent agreement was observed between linear and Bayesian two-concentration methods (r = 0.963, clinical agreement = 87.4%) and Bayesian two-concentration and one-concentration methods (r = 0.931, clinical agreement = 88.5%); however, a degree of variability was noted with 95% LOA −99 to 76 (MD = −11.5 mg*h/L) and −92 to 113 (MD = −10.4 mg*h/L), for the respective comparisons. The agreement between linear and Bayesian one-concentration approaches was less than prior comparisons (r = 0.823, clinical agreement = 76.8%) and demonstrated the greatest amount of variability with 95% LOA −197 to 153 (MD = −21.9 mg*h/L). Conclusions: Linear and Bayesian two-concentration methods demonstrated high-level agreement with acceptable variability and may be considered comparable to estimate vancomycin AUC24. As linear and Bayesian one-concentration methods demonstrated significant variability and suboptimal agreement, concerns exist surrounding the interchangeability of these methods in clinical practice, particularly at higher extremes of AUC24.
KW - Bayesian
KW - area under the curve
KW - pharmacodynamics
KW - pharmacokinetics
KW - therapeutic drug monitoring
KW - vancomycin
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U2 - 10.1002/phar.2670
DO - 10.1002/phar.2670
M3 - Article
C2 - 35134264
AN - SCOPUS:85124769620
SN - 0277-0008
VL - 42
SP - 284
EP - 291
JO - Pharmacotherapy
JF - Pharmacotherapy
IS - 4
ER -