Systematic Review of Vancomycin Population Pharmacokinetic Models in Critically Ill Patients: A Focus on Model...

Objective: Several population pharmacokinetic (PopPK) studies of vancomycin in intensive care unit (ICU) patients have been reported. However, substantial heterogeneity exists across these studies, and their predictive performance remains uncertain owing to a lack of external validation. This study systematically reviews published PopPK models of vancomycin in critically ill patients and externally validated selected models using real-world data, with the aim of clarifying factors contributing to variability in vancomycin pharmacokinetic parameters and identifying knowledge gaps that require further investigation. Methods: Databases such as PubMed, EMBASE, and the Cochrane Library were searched for studies on vancomycin PopPK models in critically ill patients constructed using nonlinear mixed-effects methods. External validation of selected models was performed using the NONMEM software with external datasets. Results: A total of 16 PopPK studies of vancomycin in ICU patients were included. Factors such as renal function indicators, concomitant renal replacement therapy (RRT), and demographic characteristics significantly influenced vancomycin PopPK parameters in ICU patients. Serum creatinine levels and concomitant RRT significantly affected vancomycin clearance, with clearance increasing with higher creatinine clearance or the presence of RRT, whereas body weight significantly influenced the apparent volume of distribution, which increased with increasing body weight. External validation was performed for three of these models, but all models showed unsatisfactory external validation results, with poor predictive capability for the external validation datasets. Conclusions: The reported studies show variations in vancomycin PopPK parameters among ICU patients, with significant inter-individual variability. Clinical dosing should be adjusted based on patients' concomitant therapies, renal function, and body weight. Existing published models lack external validation, and the results of external validation have not been satisfactory. It is recommended that PopPK models undergo external validation to assess their predictive performance before application. Additionally, future research should place greater emphasis on external validation to thoroughly evaluate model performance.