Cook Sarah F, Roberts Jessica K, Samiee-Zafarghandy Samira, Stockmann Chris, King Amber D, Deutsch Nina, Williams Elaine F, Allegaert Karel, Wilkins Diana G, Sherwin Catherine M T, van den Anker John N
Center for Human Toxicology, Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA.
Division of Clinical Pharmacology, Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA.
Clin Pharmacokinet. 2016 Jan;55(1):107-19. doi: 10.1007/s40262-015-0301-3.
The aims of this study were to develop a population pharmacokinetic model for intravenous paracetamol in preterm and term neonates and to assess the generalizability of the model by testing its predictive performance in an external dataset.
Nonlinear mixed-effects models were constructed from paracetamol concentration-time data in NONMEM 7.2. Potential covariates included body weight, gestational age, postnatal age, postmenstrual age, sex, race, total bilirubin, and estimated glomerular filtration rate. An external dataset was used to test the predictive performance of the model through calculation of bias, precision, and normalized prediction distribution errors.
The model-building dataset included 260 observations from 35 neonates with a mean gestational age of 33.6 weeks [standard deviation (SD) 6.6]. Data were well-described by a one-compartment model with first-order elimination. Weight predicted paracetamol clearance and volume of distribution, which were estimated as 0.348 L/h (5.5 % relative standard error; 30.8 % coefficient of variation) and 2.46 L (3.5 % relative standard error; 14.3 % coefficient of variation), respectively, at the mean subject weight of 2.30 kg. An external evaluation was performed on an independent dataset that included 436 observations from 60 neonates with a mean gestational age of 35.6 weeks (SD 4.3). The median prediction error was 10.1 % [95 % confidence interval (CI) 6.1-14.3] and the median absolute prediction error was 25.3 % (95 % CI 23.1-28.1).
Weight predicted intravenous paracetamol pharmacokinetics in neonates ranging from extreme preterm to full-term gestational status. External evaluation suggested that these findings should be generalizable to other similar patient populations.
本研究的目的是建立一个针对早产和足月新生儿静脉注射对乙酰氨基酚的群体药代动力学模型,并通过在外部数据集中测试其预测性能来评估该模型的可推广性。
在NONMEM 7.2中根据对乙酰氨基酚浓度 - 时间数据构建非线性混合效应模型。潜在的协变量包括体重、胎龄、出生后年龄、月经后年龄、性别、种族、总胆红素和估计肾小球滤过率。使用外部数据集通过计算偏差、精密度和标准化预测分布误差来测试模型的预测性能。
模型构建数据集包括来自35名新生儿的260个观察值,平均胎龄为33.6周[标准差(SD)6.6]。数据用具有一级消除的单室模型得到了很好的描述。体重预测了对乙酰氨基酚的清除率和分布容积,在平均受试者体重2.30 kg时,清除率估计为0.348 L/h(相对标准误差5.5%;变异系数30.8%),分布容积估计为2.46 L(相对标准误差3.5%;变异系数14.3%)。对一个独立数据集进行了外部评估,该数据集包括来自60名新生儿的436个观察值,平均胎龄为35.6周(SD 4.3)。中位预测误差为10.1%[95%置信区间(CI)6.1 - 14.3],中位绝对预测误差为25.3%(95% CI 23.1 - 28.1)。
体重预测了从极早产儿到足月妊娠状态的新生儿静脉注射对乙酰氨基酚的药代动力学。外部评估表明这些发现应可推广到其他类似患者群体。