Prediction Accuracy of Area under the Concentration-Time Curve of Vancomycin by Bayesian Approach Using Creatinine-based Equations of Estimated Kidney Function in Bedridden Elderly Japanese Patients

抄録

An administration plan for vancomycin (VCM) in bedridden elderly patients has not been established. This retrospective study aimed to evaluate the prediction accuracy of the area under the concentration-time curve (AUC) of VCM by the Bayesian approach using creatinine-based equations of estimated kidney function in such patients. Kidney function was estimated using the Japanese equation of estimated glomerular filtration rate (eGFR) and the Cockcroft–Gault equation of estimated creatinine clearance (eCCr). eCCr (SCr+0.2) was calculated by substituting the serum creatinine (SCr) level + 0.2 mg/dL into the Cockcroft–Gault equation. For eGFR/0.789, eGFR, eCCr, and eCCr (SCr+0.2), the AUC values were calculated by the Bayesian approach using the TDM software, BMs-Pod (ver 8.06) and denoted as AUC_eGFR/0.789, AUC_eGFR, AUC_eCCr, and AUC_{eCCr (SCr+0.2)} respectively. The reference AUC (AUC_REF) was calculated by applying VCM's peak and trough steady-state concentrations to first-order pharmacokinetic equations. The medians (range) of AUC_eGFR/0.789/AUC_REF, AUC_eGFR/AUC_REF, AUC_eCCr/AUC_REF, and AUC_{eCCr (SCr+0.2)}/AUC_REF were 0.88 (0.74–0.93), 0.90 (0.79–1.04), 0.92 (0.81–1.07), and 1.00 (0.88–1.11), respectively. Moreover, the percentage of patients within 10% of the AUC_REF, defined as |Bayesian-estimated AUC − AUC_REF|<AUC_REF×0.1, was the highest (86%) in AUC_{eCCr (SCr+0.2)}. These results suggest that the Bayesian approach using eCCr (SCr+0.2) has the highest prediction accuracy for the AUC_REF in bedridden elderly patients. Although further studies are required with more accurate determination methods of the CCr and AUC, our findings highlight the potential of eCCr (SCr+0.2) for estimating VCM's AUC by the Bayesian approach in such patients.