Leveraging Clinical Data to Enhance the Performance Evaluation of Ceftriaxone Population Pharmacokinetic Models in Children
摘要
Sepsis affects approximately 8% of pediatric intensive care unit (PICU) admissions in high-income countries. Ceftriaxone, a broad-spectrum beta-lactam antibiotic, is widely used for treating severe infections and bacterial meningitis in children. Despite its frequent use, limited studies address the population pharmacokinetic (popPK) of ceftriaxone in pediatrics. External validation of popPK models is essential to confirm their suitability for individualized dosing in PICU patients, enabling selection of the model best suited to this population.
MethodsThis study used data from the EXPAT Kids study, a prospective pharmacokinetics /pharmacodynamics (PK/PD) study. The included popPK models were implemented in NONMEM, with diagnostic goodness-of-fit and visual predictive check analyses performed to assess model accuracy. Predictive performance was evaluated using the relative prediction error, relative root mean square error, and mean (absolute) percentage error.
ResultsThe predictive performance of the evaluated models varied widely. The included models showed only modest performance and generally seemed to overpredict ceftriaxone concentrations. Unbound ceftriaxone popPK models did not perform adequately. None of the models met all the predefined thresholds for accuracy and precision.
ConclusionsOur external dataset comprised high ceftriaxone trough concentrations, indicating re-evaluation of current ceftriaxone dosing regimens to minimize the risk of overdosing and prevent toxicity. Future research should focus on the fine dosing balance for ceftriaxone, especially in patients with meningitis, by considering adequate exposure while preventing high trough concentrations. Model-informed precision dosing may enhance the use of the optimal individual dosage for critically ill children. However, our findings highlight the importance of externally evaluating ceftriaxone popPK models in the PICU population.