Evaluation of Limited Sampling Strategies for Bayesian Estimation of Daptomycin Area Under the Concentration–Time Curve: A Short Communication

Abstract

Increasing evidence supports daptomycin therapeutic drug monitoring. The author's reference center used to perform therapeutic drug monitoring in patients who receive high-dose daptomycin for bone and joint infections, with a three-sample strategy to estimate the daptomycin daily area under the concentration-time curve (AUC). The objective of this study was to evaluate simpler strategies based on only 2 or 1 sample(s). Methods:The authors used the BestDose software to estimate the daptomycin AUC after Bayesian posterior estimation of individual pharmacokinetic (PK) parameters at steady state. The reference AUC (AUC full ) was based on 3 samples obtained predose (T0) and approximately 1 hour (T1) and 6 hours (T6) after the start of a 30-minute infusion of IV daptomycin. It was compared with the AUC based on all possible 2-sample and 1-sample strategies. Bias, imprecision, regression, and Bland-Altman plots were used to assess the performance of the alternative strategies.

Daptomycin Exposure Prediction With a Limited Sampling Strategy

“…Pai and colleagues elaborated a model to predict DAP AUC 0-24 in patients receiving DAP doses ,8 mg/kg daily using a Bayesian model, whereas Toulup et al used three-point curves and a Bayesian model, 14 along with other authors. 15,16 The aim of the study was to develop and validate the estimation of DAP AUC 0-24 with a limited sampling strategy (LSS) in patients with severe infections (suspected or confirmed infective endocarditis) treated with higher DAP doses (8-12 mg/kg) using a multiple regression approach on samples within the first 2 hours, as disease severity requires prompt and correct therapy in terms of molecules and dosages.…”