Comparison of Bayesian-derived and first-order analytic equations for calculation of vancomycin area under the curve

Katie B. Olney, Katie L. Wallace, Ryan P. Mynatt, David S. Burgess, Kaitlyn Grieves, Austin Willett, Johann Mani, Alexander H. Flannery

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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.

Original languageEnglish
Pages (from-to)284-291
Number of pages8
Issue number4
StatePublished - Apr 2022

Bibliographical note

Funding Information:
Statistical support was provided by Dr. Arnold Stromberg, PhD. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Funding Information:
This publication is the result of research funded by the ACCP Foundation Futures Grant Resident Investigator Award (2020–2021). Bayesian software was provided on a trial basis by InsightRx™ at no cost. The authors have no additional conflicts of interest to disclose.

Publisher Copyright:
© 2022 Pharmacotherapy Publications, Inc.


  • Bayesian
  • area under the curve
  • pharmacodynamics
  • pharmacokinetics
  • therapeutic drug monitoring
  • vancomycin

ASJC Scopus subject areas

  • Pharmacology (medical)


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