AIMS: To characterize the population pharmacokinetics of netilmicin, an aminoglycoside antibiotic, in adult urology patients and to develop a covariate model for improved dose titration. METHODS: Data from 62 adult patients (55 male, seven female), undergoing urological surgery and treated withnetilmicinfor short-term prophylaxis, were evaluated retrospectively. The group had (median, range) ages 68, 31-92 years, weights 72, 43-106 kg and heights 167, 148-182 cm. No patient showed renal impairment before netilmicin treatment (serum creatinine </=1.9 mg dl-1). Netilmicin (100 mg) was administered as a maximum of four successive intravenous infusions of 30 min, at 8-h intervals. A total of five blood samples were collected from each patient. Prior to analysis, the dataset was divided into 'index' (n = 44) and 'validation' (n = 18) groups at random. The time courses of netilmicin concentrations from all subjects were analysed using a mixed effects, population, nonlinear modelling package (WinNonMix). For covariate model development, a stepwise procedure was used with backward elimination followed by forward inclusion based on age, sex, weight, height, creatinine clearance and type of surgery. The final covariate model parameters from the index group were used to simulate concentrations in the validation group and the bias and precision were compared with the observations. RESULTS: A bi-compartmental open model with a proportional residual error best described the data. The population parameters for central and peripheral volumes of distribution were (typical population value [interindividual CV%]) Vc = 14.5 l [56%] and Vp = 10.2 l [not estimated], and the systemic and intercompartmental clearances were CL = 3.9 l h-1[42%] and CLQ = 10.1 l h-1[not estimated], respectively. The final population covariate relationships were based on sex (SEX) and creatinine clearance (CrCL): (Vc, l) = 18.9 - 5.9 x SEX [29%] and (CL, l h-1) = 0.06 x CrCL [33%]. Compared with the observations in the validation group, this model showed a bias (95% confidence interval) of -0.028 (-0.28, 0.25) and precision of 1.22 (0.78, 1.34). CONCLUSION: Bi-compartmental pharmacokinetic parameters of netilmicin have been estimated from clinical data in urological surgery patients using a population approach. A given single dose results in large variability in plasma concentrations and thus the population covariate final model can be used for direct estimation of initial dosing in patients.
RCT Entities:
AIMS: To characterize the population pharmacokinetics of netilmicin, an aminoglycoside antibiotic, in adult urology patients and to develop a covariate model for improved dose titration. METHODS: Data from 62 adult patients (55 male, seven female), undergoing urological surgery and treated with netilmicin for short-term prophylaxis, were evaluated retrospectively. The group had (median, range) ages 68, 31-92 years, weights 72, 43-106 kg and heights 167, 148-182 cm. No patient showed renal impairment before netilmicin treatment (serum creatinine </=1.9 mg dl-1). Netilmicin (100 mg) was administered as a maximum of four successive intravenous infusions of 30 min, at 8-h intervals. A total of five blood samples were collected from each patient. Prior to analysis, the dataset was divided into 'index' (n = 44) and 'validation' (n = 18) groups at random. The time courses of netilmicin concentrations from all subjects were analysed using a mixed effects, population, nonlinear modelling package (WinNonMix). For covariate model development, a stepwise procedure was used with backward elimination followed by forward inclusion based on age, sex, weight, height, creatinine clearance and type of surgery. The final covariate model parameters from the index group were used to simulate concentrations in the validation group and the bias and precision were compared with the observations. RESULTS: A bi-compartmental open model with a proportional residual error best described the data. The population parameters for central and peripheral volumes of distribution were (typical population value [interindividual CV%]) Vc = 14.5 l [56%] and Vp = 10.2 l [not estimated], and the systemic and intercompartmental clearances were CL = 3.9 l h-1[42%] and CLQ = 10.1 l h-1[not estimated], respectively. The final population covariate relationships were based on sex (SEX) and creatinine clearance (CrCL): (Vc, l) = 18.9 - 5.9 x SEX [29%] and (CL, l h-1) = 0.06 x CrCL [33%]. Compared with the observations in the validation group, this model showed a bias (95% confidence interval) of -0.028 (-0.28, 0.25) and precision of 1.22 (0.78, 1.34). CONCLUSION: Bi-compartmental pharmacokinetic parameters of netilmicin have been estimated from clinical data in urological surgery patients using a population approach. A given single dose results in large variability in plasma concentrations and thus the population covariate final model can be used for direct estimation of initial dosing in patients.
Authors: F C Luft; D R Brannon; L L Stropes; R J Costello; R S Sloan; D R Maxwell Journal: Antimicrob Agents Chemother Date: 1978-09 Impact factor: 5.191
Authors: Catherine M T Sherwin; Roland S Broadbent; Natalie J Medlicott; David M Reith Journal: Eur J Clin Pharmacol Date: 2008-08-07 Impact factor: 2.953