Llanos-Paez C C, Staatz C E, Lawson R, Hennig S
School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia
School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia.
Antimicrob Agents Chemother. 2017 Jul 25;61(8). doi: 10.1128/AAC.00205-17. Print 2017 Aug.
To ensure the safe and effective dosing of gentamicin in children, therapeutic drug monitoring (TDM) is recommended. TDM utilizing Bayesian forecasting software is recommended but is unavailable, as no population model that describes the pharmacokinetics of gentamicin in pediatric oncology patients exists. This study aimed to develop and externally evaluate a population pharmacokinetic model of gentamicin to support personalized dosing in pediatric oncology patients. A nonlinear mixed-effect population pharmacokinetic model was developed from retrospective data. Data were collected from 423 patients for model building and a further 52 patients for external evaluation. A two-compartment model with first-order elimination best described the gentamicin disposition. The final model included renal function (described by fat-free mass and postmenstrual age) and the serum creatinine concentration as covariates influencing gentamicin clearance (CL). Final parameter estimates were as follow CL, 5.77 liters/h/70 kg; central volume of distribution, 21.6 liters/70 kg; peripheral volume of distribution, 13.8 liters/70 kg; and intercompartmental clearance, 0.62 liter/h/70 kg. External evaluation suggested that current models developed in other pediatric cohorts may not be suitable for use in pediatric oncology patients, as they showed a tendency to overpredict the observations in this population. The final model developed in this study displayed good predictive performance during external evaluation (root mean square error, 46.0%; mean relative prediction error, -3.40%) and may therefore be useful for the personalization of gentamicin dosing in this cohort. Further investigations should focus on evaluating the clinical application of this model.
为确保儿童庆大霉素给药的安全有效,建议进行治疗药物监测(TDM)。推荐使用基于贝叶斯预测软件的TDM,但由于不存在描述儿科肿瘤患者庆大霉素药代动力学的群体模型,该方法无法使用。本研究旨在开发并外部评估庆大霉素的群体药代动力学模型,以支持儿科肿瘤患者的个体化给药。通过回顾性数据建立了非线性混合效应群体药代动力学模型。收集了423例患者的数据用于模型构建,并另外收集了52例患者的数据用于外部评估。具有一级消除的二室模型最能描述庆大霉素的处置过程。最终模型纳入了肾功能(由去脂体重和月经后年龄描述)和血清肌酐浓度作为影响庆大霉素清除率(CL)的协变量。最终参数估计如下:CL为5.77升/小时/70千克;中央分布容积为21.6升/70千克;外周分布容积为13.8升/70千克;以及室间清除率为0.62升/小时/70千克。外部评估表明,其他儿科队列中开发的现有模型可能不适用于儿科肿瘤患者,因为它们倾向于高估该人群的观察值。本研究中开发的最终模型在外部评估期间表现出良好的预测性能(均方根误差为46.0%;平均相对预测误差为-3.40%),因此可能有助于该队列中庆大霉素给药的个体化。进一步的研究应侧重于评估该模型的临床应用。