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Background <p>Current guidelines for vancomycin dosing and monitoring recommend calculating area under the concentration–time curve (AUC) using a Bayesian approach. However, Bayesian approaches are challenging, requiring specialised software and expertise. Thus, simpler AUC calculation methods are required.</p> Aim <p>To develop and validate a nomogram to estimate the AUC of vancomycin based on the mathematical equation of the one-compartment model, and to investigate the clinical applicability of the apparent volume of distribution (Vd<sub>,app</sub>) estimated from the first peak concentration after the first dose as an alternative to the volume of distribution.</p> Methods <p>AUC values based on the nomogram and the Bayesian approach were compared in 51 patients who received vancomycin between May 2022 and December 2023. The first peak concentration and steady-state trough concentrations were measured in all patients, and Vd<sub>,app</sub> was calculated using the following formula: Vd<sub>,app</sub> = First dose / the first peak concentration. The regression line was estimated using the Passing–Bablok method, and the correlation was evaluated using Kendall’s tau.</p> Results <p>The regression line relating the AUC based on the nomogram to the Bayesian approach had a slope of 0.988 (95% CI, 0.855, 1.131) and an intercept of 5.35 (95% CI, − 48.59, 64.26). Kendall’s tau was 0.643 (<i>P</i> &lt; 0.01), indicating a positive correlation.</p> Conclusion <p>The estimation method utilising AUC nomograms and Vd<sub>,app</sub> represents a straightforward approach with accuracy comparable to that of the Bayesian method, suggesting its potential for clinical application. However, its implementation in cases of high clearance or in patients with severe infections warrants careful consideration.</p>

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Use of nomograms based on the one-compartment model in the estimation of area under the blood concentration–time curve of vancomycin: a retrospective cohort study

  • 期刊论文

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  • 发表日期：

    2025年8月4日

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  • Go Okamoto,
  • Aya Kawakami,
  • Daisuke Ito,
  • Miki Sawai,
  • Kanae Okano,
  • Emiko Kobayashi

摘要

Background

Current guidelines for vancomycin dosing and monitoring recommend calculating area under the concentration–time curve (AUC) using a Bayesian approach. However, Bayesian approaches are challenging, requiring specialised software and expertise. Thus, simpler AUC calculation methods are required.

Aim

To develop and validate a nomogram to estimate the AUC of vancomycin based on the mathematical equation of the one-compartment model, and to investigate the clinical applicability of the apparent volume of distribution (Vd,app) estimated from the first peak concentration after the first dose as an alternative to the volume of distribution.

Methods

AUC values based on the nomogram and the Bayesian approach were compared in 51 patients who received vancomycin between May 2022 and December 2023. The first peak concentration and steady-state trough concentrations were measured in all patients, and Vd,app was calculated using the following formula: Vd,app = First dose / the first peak concentration. The regression line was estimated using the Passing–Bablok method, and the correlation was evaluated using Kendall’s tau.

Results

The regression line relating the AUC based on the nomogram to the Bayesian approach had a slope of 0.988 (95% CI, 0.855, 1.131) and an intercept of 5.35 (95% CI, − 48.59, 64.26). Kendall’s tau was 0.643 (P < 0.01), indicating a positive correlation.

Conclusion

The estimation method utilising AUC nomograms and Vd,app represents a straightforward approach with accuracy comparable to that of the Bayesian method, suggesting its potential for clinical application. However, its implementation in cases of high clearance or in patients with severe infections warrants careful consideration.