Effect of various estimates of renal function on prediction of vancomycin concentration by the population mean and Bayesian methods

Objective: Renal function was estimated in 129 elderly patients with methicillin-resistant Staphylococcus aureus (MRSA) who were treated with vancomycin (VCM). The estimation was performed by substituting serum creatinine (SCR) measured enzymatically and a value converted using the Jaffe method into the Cockcroft-Gault and Modification of Diet in Renal Disease (MDRD) equations. The serum trough level was predicted from three estimates of renal function by the population mean (PM) and Bayesian methods and the predictability was assessed. Methods: Two-compartment model-based Japanese population parameters for VCM were used, and the mean prediction error (ME) and root mean squared error (RMSE) were calculated as indices of bias and accuracy, respectively, for predictions by the PM and Bayesian methods. Results: The PM method gave the highest correlation with the measured value using the estimate of renal function obtained by substituting the Jaffe-converted SCR into the Cockcroft-Gault equation. There was no positive or negative bias in the ME and the value was significantly smaller than for other predicted data (P < 0 center dot 05). RMSE was also the smallest, indicating that this method increases the predictability of the serum VCM trough level. While, ME showed a negative bias for all values predicted by the Bayesian method, both the ME and RMSE were very small. Conclusion: In the application of the PM method for VCM treatment of elderly patients with MRSA, substitution of SCR based on the Jaffe method into the Cockcroft-Gault equation increases the predictability of the serum VCM trough level. The Bayesian method predicted the serum VCM trough level with high accuracy using any of the estimates of renal function.