Validation of a Pediatric Population Pharmacokinetic Model for Vancomycin. Issue 3 (June 2015)

• Record Type: Journal Article
• Authors: Hahn, Andrea; Frenck, Robert W.; Zou, Yuanshu; Vinks, Alexander A.
• Is Part Of: Therapeutic drug monitoring. Volume 37:Issue 3(2015:Jun.)
• Publication Date: 2015-06
• Subjects: vancomycin -- population pharmacokinetic model -- pediatric -- MRSA; Pharmacokinetics -- Periodicals; Patient monitoring -- Periodicals; Drugs -- Analysis -- Periodicals; Body fluids -- Analysis -- Periodicals; Drug Therapy -- Periodicals; Monitoring, Physiologic -- Periodicals; Pharmacology -- Periodicals; 615.7
• DOI: 10.1097/FTD.0000000000000153
• Languages: English
• ISSNs: 0163-4356

Abstract

Abstract : Background: Vancomycin is often required to treat serious infections in children, including methicillin-resistant Staphylococcus aureus infections. The pharmacodynamic index that best predicts efficacy with vancomycin use for methicillin-resistant S. aureus infection in adults is the 24-hour area under the curve (AUC) over the minimum inhibitory concentration. Although multiple pediatric population pharmacokinetic (PK) vancomycin models have been published, few use Bayesian optimization. The current standard of care remains measuring vancomycin serum trough concentrations as a surrogate marker of AUC. Materials and Methods: A prospective validation of a pediatric population PK model of vancomycin was performed. Hospitalized children younger than 18 years receiving vancomycin at Cincinnati Children's Hospital Medical Center were invited to participate. Peak, trough, and random vancomycin serum concentrations were used for Bayesian estimation of individual PK parameters. Model covariates included age, weight, and serum creatinine. To evaluate the predictive performance of the model, precision and bias were measured and compared using the 95% confidence interval. Results: Fifteen subjects were enrolled; 13 subjects had vancomycin serum concentrations drawn per protocol. Of those 13 subjects, the median age was 6 years and 54% were male. Significant medical conditions included cancer (54%), lung disease (23%), neurologic disorders (23%), and prior transplantation (15%). The initial serum creatinine was normal (median, 0.33; interquartile range, 0.23–0.4 mg/dL), and none had underlying renal dysfunction. Equivalence of bias and precision between the original model validation and the Cincinnati Children's Hospital Medical Center validation were found. Conclusions: Pediatric population PK models for vancomycin with Bayesian estimation can be used to reliably predict vancomycin exposure in children. Using AUC instead of trough serum concentrations alone can provide an opportunity to maximally optimize vancomycin administration in children.