Amélie Marsot1,2, F Gallais3, C Galambrun4, C Coze4, O Blin5,3, N Andre4,6, R Guilhaumou5,3. 1. Service de Pharmacologie Clinique et Pharmacovigilance, Hôpital de la Timone, 264 rue Saint Pierre, 13385, Marseille Cedex 5, France. amelie.marsot@ap-hm.fr. 2. Aix Marseille Université, Pharmacologie Intégrée Interface Clinique et Industriel, Institut des Neurosciences Timone-CNRS 7289, 13385, Marseille, France. amelie.marsot@ap-hm.fr. 3. Aix Marseille Université, Pharmacologie Intégrée Interface Clinique et Industriel, Institut des Neurosciences Timone-CNRS 7289, 13385, Marseille, France. 4. Service d'Hématologie et Oncologie Pédiatrique, Hôpital de la Timone, Marseille, France. 5. Service de Pharmacologie Clinique et Pharmacovigilance, Hôpital de la Timone, 264 rue Saint Pierre, 13385, Marseille Cedex 5, France. 6. INSERM, UMR 911, Centre de Recherche en Oncologie biologique et en Oncopharmacologie, Aix-Marseille University, Marseille, France.
Abstract
BACKGROUND: The application of population pharmacokinetic models and Bayesian methods offers the potential to develop individualized therapeutic approaches. OBJECTIVES: The current study presents an external evaluation of a vancomycin pharmacokinetic model in a pediatric cancer population and proposes an easy-to-use chart for clinicians for a priori vancomycin schedule adaptation to achieve target concentration. METHODS: External evaluation of a population pharmacokinetic model of vancomycin administered via continuous infusion was realized in a new retrospective dataset of pediatric patients with cancer. The published population pharmacokinetic model was implemented in NONMEM 7.3 with the structural and variance parameter values set equal to estimates previously reported. Predictive performance was assessed by quantifying bias and accuracy of model prediction. Normalized prediction distribution errors were also evaluated. Dosage simulations were performed according to the target concentration. RESULTS: A total of 77 patients were included in this study, representing 146 vancomycin courses and 289 concentrations. The model adequately predicted vancomycin concentrations (median prediction error % of - 9.4%, median |PE|% of 24.1%). Based on simulation results, vancomycin dosage (mg/kg) should be adapted for each child on the basis of body weight and cyclosporine coadministration. CONCLUSION: The model previously proposed by Guilhaumou et al. in pediatric patients with solid or hematological malignant disease was externally validated. Simulations have enabled the description of new dosage schedules and creation of a chart to help clinicians adapt vancomycin dosage.
BACKGROUND: The application of population pharmacokinetic models and Bayesian methods offers the potential to develop individualized therapeutic approaches. OBJECTIVES: The current study presents an external evaluation of a vancomycin pharmacokinetic model in a pediatric cancer population and proposes an easy-to-use chart for clinicians for a priori vancomycin schedule adaptation to achieve target concentration. METHODS: External evaluation of a population pharmacokinetic model of vancomycin administered via continuous infusion was realized in a new retrospective dataset of pediatric patients with cancer. The published population pharmacokinetic model was implemented in NONMEM 7.3 with the structural and variance parameter values set equal to estimates previously reported. Predictive performance was assessed by quantifying bias and accuracy of model prediction. Normalized prediction distribution errors were also evaluated. Dosage simulations were performed according to the target concentration. RESULTS: A total of 77 patients were included in this study, representing 146 vancomycin courses and 289 concentrations. The model adequately predicted vancomycin concentrations (median prediction error % of - 9.4%, median |PE|% of 24.1%). Based on simulation results, vancomycin dosage (mg/kg) should be adapted for each child on the basis of body weight and cyclosporine coadministration. CONCLUSION: The model previously proposed by Guilhaumou et al. in pediatric patients with solid or hematological malignant disease was externally validated. Simulations have enabled the description of new dosage schedules and creation of a chart to help clinicians adapt vancomycin dosage.
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