External Evaluation of Vancomycin Models

Introduction

Current clinical evidence supports area under the concentration-time curve (AUC) rather than trough concentrations as a more rational target for vancomycin therapy (1). In mid-2019 practice at Auckland District Health Board Hospitals transitioned from trough concentration to AUC guided dosing supported by Bayesian forecasting using the GAVamycin model implemented in NextDose (www.nextdose.org).

To support ongoing quality improvement, a before and after study was conducted to evaluate target concentration intervention for vancomycin.

Aims

To evaluate the predictive performance published vancomycin non-linear mixed effect models (2) with the GAVamycin model.

Methods

The before and after cohorts comprised of consecutive patients admitted to Auckland City or Starship Children’s Hospital from 1 August 2018 to 28 February 2019 (before) or 1 May to 30 September 2020 (after), with at least one vancomycin concentration. Each of the evaluated models (3-8) were used to predict the observed concentration for each individual given their covariates, doses and measured concentrations. Models were run using NONMEM 7.4.4 with gfortran-64 compiler.

Prediction error (PE) was calculated from the model prediction of each observed concentration. Model performance was evaluated quantitatively with mean PE (MPE), root mean square error (RMSE), and objective function value (OFV) (MAXEVAL=0).

Results

Data was collected from 263 individuals with 1190 concentrations.

MODEL MPE (mg/L) [95% CI] RMSE MPE (mg/L) OFV
GAVamycin 0.39 [0.15; 0.64] 4.28 5230
Goti_2018 -0.39 [-0.58; -0.2] 3.32 5062
Mangin_2014 0.57 [0.51; 1.08] 4.37 5883
Medellin_2016 -0.4 [0.32; 0.82] 3.76 5286
Roberts_2011 -0.5 [-0.70; -0.29] 3.62 6755
Thomson_2009 -0.27 [-0.46; -0.09] 3.3 5484

Conclusion

Predictions using the GAVamycin model were accurate, precise and appear suitable for routine clinical use.

References

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