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EXTERNAL EVALUATION OF POPULATION PHARMACOKINETIC MODELS FOR VANCOMYCIN IN ADULT PATIENTS TREATED AT SAINT PAUL HOSPITAL
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Abstract
Objective: To improve the quality of TDM vancomycin service at Saint Paul General Hospital, we screened and determined a suitable population pharmacokinetic (POP PK) model for concentration data from Saint Paul General Hospital patients, leading to a precise dosing correction tool using the Bayesian method. Methods and subjects: The predictive ability of vancomycin POP PK models was evaluated using a data set of vancomycin concentrations collected at Saint Paul General Hospital from a group of patients undergoing TDM vancomycin. Results: The performance of the tested models varied with our data set. The best fit model is Yamamoto's vancomycin POP PK model, which was published in 2009, with a mean absolute prediction error (MAPE) of 9.96% - excellent prediction level, and mean prediction error (MPE) of 0.637 mg/l (<2.5 mg/l –Limit of quantification). Conclusion: Yamamoto's model, published in 2009, is the most appropriate for the patient population at Saint Paul General Hospital. These findings could be utilized to create a future Bayesian dosage correction tool.
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Keywords
vancomycin, TDM, POP PK, external validation
References
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