非线性混合效应模型法估算癫痫患者卡马西平的群体药动学参数

目的:建立癫痫患者卡马西平(CBZ)的群体药动学(PPK)模型。方法:采集我院服用CBZ的270例门诊癫痫患者的稳态血药浓度数据(共316个样本)以及患者相关资料数据。应用非线性混合效应模型(NONMEM)法估算癫痫患者CBZ的PPK参数值,建立PPK模型。并运用自举法(Bootstrap)验证模型的可靠性。结果:年龄(AGE)、每日服药剂量(DKG)、体质量(BW)均为CBZ清除率(CL)的影响因素。最终模型:当AGE≤14岁时,CL(L/h)=2.55+0.013×(AGE-15)]×(DKG/0.011)0.443×(BW/40)0.392;AGE>14岁时,CL(L/h)=2.55×(DKG/0.011)0.443×(BW/40)0.392。表观分布容积(Vd)=85L。经Bootstrap法验证,本模型稳定、可靠。结论:用NONMEM软件成功建立我院癫痫患者服用CBZ的PPK模型。根据本院癫痫患者的PPK模型,结合患者DKG、BW和合并用药可估算其CL,优化临床个体化用药方案。

Evaluation of Population Pharmacokinetic Parameters of Carbamazepine in Epileptic Patients by NONMEM

OBJECTIVE： To set up a population pharmacokinetics （PPK） model of Carbamazepine（CBZ） in epileptic patients. METHODS： The data of CBZ plasma concentrations of 270 epileptic patients in outpatient department were collected （n=36） as well as related information of patients. PPK parameters of CBZ in epileptic patients were calculated using NONMEM software to set up PPK model. The reliability of model was validated using Bootstrap. RESULTS： The clearance rate（CL） of CBZ was influenced by age, CKG and body weight （BW）. The final models of CBZ were as follows： CL （L/h）=2.55＋0.013×（Age-15）]×（DKG/0.011）0.443×（BW/40）0.392 when the age of patients were lower than 14;When the age of patients were larger than 14, CL （L/h）=2.55×（DKG/0.011）0.443×（BW/40）0.392 . Vd=85 L. Results of bootstrap showed established model was stable and reliable. CONCLUSION： PPK models of CBZ in epileptic patients of our hospital have been established successfully using NONMEM software. The clearance rate of CBZ can be calculated according to PPK model, DKG, BW and drug combination. Individual drug therapy regimen can be optimized.