Title |
Assessing Predictive Performance of Published Population Pharmacokinetic Models of Intravenous Tobramycin in Pediatric Patients
|
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Published in |
Antimicrobial Agents and Chemotherapy, May 2016
|
DOI | 10.1128/aac.02654-15 |
Pubmed ID | |
Authors |
Celeste Bloomfield, Christine E. Staatz, Sean Unwin, Stefanie Hennig |
Abstract |
Several population pharmacokinetic models describe the dose-exposure relationship of tobramycin in paediatric patients. Before implementing these models in clinical practice for dosage adjustment their predictive performance should be externally evaluated. This study tested the predictive performance of all published population pharmacokinetic models of tobramycin developed in paediatric patients in an independent patient cohort. A literature search was conducted to identify suitable models for testing. Demographic and pharmacokinetic data were collected retrospectively from medical records of paediatric patients who had received intravenous tobramycin. Tobramycin exposure was predicted from each model. Predictive performance was assessed by comparing predictions to observations visually, calculating bias and imprecision, and through use of simulation-based diagnostics. Eight population pharmacokinetic models were identified. 269 concentration-time points from 41 paediatric patients with cystic fibrosis were collected for external evaluation. Three models consistently performed the best in all evaluations and had a mean error ranging from -0.4 to 1.8 mg/L, relative mean error from 4.9 to 29.4% and root mean square error from 47.8 to 66.9%. Simulation-based diagnostics supported these findings. Models that allowed for two-compartment disposition generally had better predictive performance than those with one-compartment disposition. Several published pharmacokinetic models of tobramycin showed reasonable low levels of bias although all models seemed to have some problems with imprecision. This suggests that knowledge of typical pharmacokinetic behaviour and patient covariate values alone without feedback concentration measurements from individual patients is not sufficient to make precise predictions. |
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