Vancomycin AUC24 Estimation for Children with Bayesian Forecasting and First-Order Equations to Update Dose Recommendations

Objectives: This retrospective study aimed to estimate vancomycin area under the curve over 24 h (AUC24) at steady state for pediatric patients from 1 month to 18 years to update the dose recommendations in a tertiary hospital. Methods: A total of 46 vancomycin treatments from 42 patients in the years 2014–2024 were analyzed. AUC24 was estimated for the initial dose regimen using Bayesian forecasting and a trough concentration (n = 32) or first-order pharmacokinetic (PK) equations and a pair of practical peak and trough concentrations at steady state (n = 14). Three published population PK models (Colin, Kloprogge, and Le models) were compared using typical parameter values (a priori predictions) to find a suitable model for Bayesian estimation. For the Le model, the effect of converting plasma creatinine (PCr) measured with IDMS-traceable enzymatic assay to Jaffe method value was evaluated using published equations. Results: Le model without enzymatic-to-Jaffe PCr conversion and the Colin model were suitable for Bayesian forecasting. These models gave similar Bayesian AUC24 estimates (a posteriori). In all 46 treatments, estimated AUC24 was within the currently recommended range of 400–600 mg·h/L in 8 (17%) treatments, below this range in 36 (78%) treatments, and above this range in 2 (4%) treatments, respectively. Estimated AUC24 was below 300 mg·h/L in 46% of treatments. Conclusions: Le and Colin models were suitable for our pediatric patients for Bayesian forecasting. AUC24 estimates for the initial dose regimen were lower than commonly recommended. A more uniform dosing policy is needed in our hospital, and higher initial doses should be considered.