ORIGINAL ARTICLE: Investigation of the prediction accuracy of vancomycin concentrations determined by patient-specific parameters as estimated by Bayesian analysis

Abstract

There have been many studies of therapeutic drug monitoring (TDM) of vancomycin (VCM) based on Bayesian analysis, but there have been no reports of the accuracy of prediction based on Bayesian-estimated patient-specific parameters. This study was conducted to compare the accuracy of prediction based on the population pharmacokinetic (PPK) method and Bayesian-estimated parameters. The subjects were 22 patients who were treated with VCM for MRSA infection and whose blood was sampled twice or more during the administration period. The concentrations between the blood samples were predicted based on the concentrations in the first blood samples based on the PPK method using mean parameters for the Japanese population and Bayesian-estimated patient-specific pharmacokinetic parameters. The mean prediction error (ME), mean absolute error (MAE) and root mean squared error (RMSE) were compared to examine the accuracy of prediction based on Bayesian-estimated patient-specific parameters. The mean measured VCM concentration was 10·43±5·19 μg/mL, whereas the mean concentration predicted based on the PPK method was 8·52±4·34 μg/mL, with an ME of -1·91, MAE of 2·93 and RMSE of 3·21. The mean concentration predicted based on patient-specific parameters was 9·62±4·95 μg/mL with ME of -0·81, MAE of 1·38 and RMSE of 1·74. The ME and MAE for the concentrations predicted using patient-specific parameters were smaller compared with those predicted using the PPK method (P=0·0471 and 0·0003, respectively), indicating superior prediction with a significant difference between approaches. Prediction using Bayesian estimates of patient-specific parameters was better than by the PPK method. However, when using patient-specific parameters it is still necessary to fully understand the clinical status of the patient and frequently determine VCM concentrations.