Ann Lab Med.  2023 Nov;43(6):554-564. 10.3343/alm.2023.43.6.554.

Evaluation of Vancomycin Area Under the Concentration–Time Curve Predictive Performance Using Bayesian Modeling Software With and Without Peak Concentration: An Academic Hospital Experience for Adult Patients Without Renal Impairment

• Kim HK
• Jeong TD

• KMID: 2552026
• DOI: http://doi.org/10.3343/alm.2023.43.6.554

Abstract

Background
The revised U.S. consensus guidelines on vancomycin therapeutic drug monitoring (TDM) recommend obtaining trough and peak samples to estimate the area under the concentration–time curve (AUC) using the Bayesian approach; however, the benefit of such two-point measurements has not been demonstrated in a clinical setting. We evaluated Bayesian predictive performance with and without peak concentration data using clinical TDM data.
Methods
We retrospectively analyzed 54 adult patients without renal impairment who had two serial peak and trough concentration measurements in a ≤1-week interval. The concentration and AUC values were estimated and predicted using Bayesian software (MwPharm++; Mediware, Prague, Czech Republic). The median prediction error (MDPE) for bias and median absolute prediction error (MDAPE) for imprecision were calculated based on the estimated AUC and measured trough concentration.
Results
AUC predictions using the trough concentration had an MDPE of –1.6% and an MDAPE of 12.4%, whereas those using both peak and trough concentrations had an MDPE of –6.2% and an MDAPE of 16.9%. Trough concentration predictions using the trough concentration had an MDPE of –8.7% and an MDAPE of 18.0%, whereas those using peak and trough concentrations had an MDPE of –13.2% and an MDAPE of 21.0%.
Conclusions
The usefulness of the peak concentration for predicting the AUC on the next occasion by Bayesian modeling was not demonstrated; therefore, the practical value of peak sampling for AUC-guided dosing can be questioned. As this study was conducted in a specific setting and generalization is limited, results should be interpreted cautiously.

Keyword

Vancomycin; Therapeutic drug monitoring; Area under the curve; Peak; Trough

Figure

• 

  Fig. 1 Flow diagram of patient and TDM data inclusion. Abbreviation: TDM, therapeutic drug monitoring.

• 

  Fig. 2 Plot depicting the estimated AUCs at all TDM occasions over time. The AUCs were estimated using (A) the trough concentration alone and (B) both trough and peak concentration data by the Bayesian program. The gray lines connect AUCs from 1st and 2nd occasions of the same patient. The points are colored according to the daily dose and shaped according to the dose changes between 1st and 2nd occasion. The points are jittered (adding a small amount of random variation to the location on the X-axis) to avoid overplotting. Abbreviations: AUC, area under the concentration–-time curve (mg∙hr/L); TDM, therapeutic drug monitoring.

• 

  Fig. 3 Scatter plots depicting the predicted AUC24 or concentration (using 1st TDM occasion data) versus reference AUC24 (estimated using 2nd TDM occasion data) or measured concentration (N=54), respectively. The predicted values were obtained using trough (left; A, C, E, G, I, K) or both trough and peak (right; B, D, F, H, J, L) concentration data. Reference values are AUCestimated[T&P] for (A) and (B); AUCestimated[T] for (C) and (D); AUCEq.(4) for (E) and (F); AUCEq.(5) for (G) and (H); trough Cmeasured for (I) and (J); and peak Cmeasured for (K) and (L). The dashed lines are the identity lines. The gray lines represent locally estimated scatterplot smoothing curves to assist visual exploration of trends. Abbreviations: AUC24, area under the concentration-–time curve normalized to 24 hours (mg∙hr/L); TDM, therapeutic drug monitoring.

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