Evaluation and Improvement of Specialized Vancomycin Pharmacokinetic Models for Pediatric Cardiovascular Intensive
Michael G McCarthy1, Ron J Keizer2, Jasmine H Hughes2
1InsightRX, 548 Market St. #88083, San Francisco, CA, 94104, USA. michael.mccarthy@insight-rx.com.
Insights
Specialized vancomycin pharmacokinetic models are not always superior for pediatric oncology or cardiovascular intensive care unit patients. A well-specified general model can be as effective, requiring case-by-case evaluation for precision dosing.
Area of Science:
- Pharmacometrics
- Pediatric Pharmacology
- Clinical Pharmacy
Background:
- Vancomycin dosing in pediatric subpopulations (e.g., oncology, cardiovascular intensive care unit) is complex due to altered pharmacokinetics.
- Existing population pharmacokinetic models aim to capture these changes, but the necessity of specialized models over general ones is unclear.
Purpose of the Study:
- To compare the predictive performance of general and specialized population pharmacokinetic models for vancomycin in pediatric oncology and cardiovascular intensive care unit (CVICU) patients.
- To guide model selection for precision vancomycin dosing in these distinct pediatric groups.
Main Methods:
- External evaluation of two general, six oncology-specific, and three CVICU-specific pharmacokinetic models.
- Comparison of predictive error, bias, and accuracy using multi-site datasets from pediatric oncology and CVICU patients.
- Refitting of best-performing models to assess potential performance improvements.
Main Results:
- Specialized models outperformed general models in pediatric CVICU patients.
- A general model (Colin 2019) outperformed specialized models in pediatric oncology patients.
- A refitted CVICU model (Shimamoto 2024) showed superior performance compared to published CVICU models.
Conclusions:
- Population pharmacokinetic models for distinct pediatric subpopulations are not inherently superior to general population models.
- Both specialized and well-specified general models can achieve adequate clinical performance.
- Model suitability must be assessed individually for each subpopulation and clinical scenario.
Background And Objective:
Dose optimization of vancomycin in distinct pediatric subpopulations is inherently complex due to altered vancomycin pharmacokinetics associated with certain conditions or circumstances, such as cancer or postoperative cardiac surgery. Numerous population pharmacokinetic models have been developed that aim to capture these alterations; however, it is currently unclear whether these specialized models are necessary, or if covariates in a well-specified general model can adequately capture pharmacokinetic variation between special subpopulations. Here, we conduct an external evaluation comparing the predictive performance of published general and specialized population pharmacokinetic models in pediatric oncology and pediatric cardiovascular intensive care unit (CVICU) patients in order to address this question, and guide model selection decisions for model-informed precision dosing of vancomycin in these subpopulations.
Methods:
The predictive error, bias, and accuracy of two general, six oncology-supporting, and three CVICU-supporting pharmacokinetic models were compared in two multi-site data sets of pediatric oncology (N = 371, 1392 drug levels, 20 sites) and pediatric CVICU (N = 219, 1136 drug levels, 11 sites) patients, respectively. The best performing model(s) in each subpopulation were refit to evaluate whether predictive performance could be further improved over the published models.
Results:
We find that although specialized models performed better than general population models for pediatric CVICU patients, a general model (Colin 2019) performed better than all specialized models for pediatric oncology patients. We additionally report a refit version of the Shimamoto 2024 model for pediatric CVICU patients, which performed better than all published CVICU-supporting models in our data set.
Conclusion:
Population pharmacokinetic models developed on distinct pediatric subpopulations are not necessarily more fit-for-purpose than models developed on a general population. Both well-specified general models and specialized models may be capable of achieving suitable clinical performance in these subpopulations, and this assessment of model fit-for-purpose must be made on a case-by-case basis.
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