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非参数建模在癫痫患者中美托咪定群体药代动力学研究。

Population Pharmacokinetics of Topiramate in Patients with Epilepsy Using Nonparametric Modeling.

机构信息

Department of Pharmacology and Therapeutics, College of Pharmacy, Kuwait University, Kuwait City, Kuwait.

Department of Pharmacy Practice, College of Pharmacy, Kuwait University, Kuwait City, Kuwait.

出版信息

Ther Drug Monit. 2023 Dec 1;45(6):797-804. doi: 10.1097/FTD.0000000000001143. Epub 2023 Oct 4.

Abstract

BACKGROUND

Topiramate (TPM) is used for the treatment of various epileptic seizures and the prevention of migraine. This study aimed to develop a population pharmacokinetic model and identify covariates that influence TPM behavior in patients with epilepsy in Kuwait.

METHODS

Data were collected retrospectively from 108 patients (2 years old and above) with epilepsy who were treated with oral TPM and 174 TPM blood samples from 3 hospitals in Kuwait from 2009 to 2016. Data were randomly divided into 2 groups for model development and validation. The population pharmacokinetic model was built using the nonparametric modeling algorithm (Pmetrics). The model was evaluated internally through the visual predictive check method and externally using a new data set.

RESULTS

A 1-compartment model with first-order elimination fitted the data well. Covariates showing a significant effect on the elimination rate constant were renal function and coadministration of carbamazepine (CBZ). The mean estimated clearance was 2.11 L/h; this was 50% higher for patients coadministered with CBZ. Age and sex were essential covariates for the volume of distribution (V). The visual predictive check of the final model could predict the measured concentrations. External validation further confirmed the favorable predictive performance of the model with low bias and imprecision for predicting the concentration in a particular population.

CONCLUSIONS

TPM elimination was increased with CBZ coadministration and was affected by renal function. Meanwhile, age and sex were the main predictors for V. The predictive performance of the final model proved to be valid internally and externally.

摘要

背景

托吡酯(TPM)用于治疗各种癫痫发作和预防偏头痛。本研究旨在建立一个群体药代动力学模型,并确定影响科威特癫痫患者 TPM 行为的协变量。

方法

从 2009 年至 2016 年,从科威特的 3 家医院收集了 108 名(2 岁及以上)接受口服 TPM 治疗的癫痫患者和 174 份 TPM 血样的数据。数据被随机分为两组进行模型开发和验证。使用非参数建模算法(Pmetrics)构建群体药代动力学模型。该模型通过可视化预测检查方法进行内部评估,并使用新数据集进行外部评估。

结果

具有一阶消除的 1 室模型很好地拟合了数据。对消除率常数有显著影响的协变量是肾功能和卡马西平(CBZ)的联合用药。估计的平均清除率为 2.11 L/h;与联合使用 CBZ 的患者相比,清除率提高了 50%。年龄和性别是分布容积(V)的重要协变量。最终模型的可视化预测检查可以预测测量浓度。外部验证进一步证实了该模型具有良好的预测性能,对特定人群的浓度预测具有低偏差和低不精密度。

结论

与 CBZ 联合使用可增加 TPM 的消除,且受肾功能影响。同时,年龄和性别是 V 的主要预测因子。最终模型的预测性能在内部和外部均被证明是有效的。

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