数学模型预测阿托伐他汀对原发性高脂血症剂量效应关系的分析

来源 :临床药物治疗杂志 | 被引量 : 0次 | 上传用户:zxd80509
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目的 :探讨采用数学模型预测阿托伐他汀对原发性高脂血症剂量效应关系的可行性。方法:选择2016年1月至2016年12月在中国中医科学院望京医院接受阿托伐他汀的原发性高脂血症患者92例,根据患者所用药物剂量分为对照组、观察组和模型组,采用数学模型预测阿托伐他汀用药剂量与治疗原发性高脂血症效果的关系。结果:通过模型预测阿托伐他汀对原发性高脂血症患者剂量为(29.16±4.25)mg·d-1,稳态剂量为(19.45±3.56)mg·d-1。对照组、观察组和预测组患者的药代动力学参数、血药浓度、甘油三酯、总胆固醇、低密度脂蛋白胆固醇和极低密度脂蛋白胆固醇比较,差异具有统计学意义(均P<0.05)。对照组与观察组药物代谢动力学参数、血药浓度、TG、TC、LDL-C和VLDL-C比较,差异具有统计学意义(均P<0.05);对照组与模型预测组药物代谢动力学参数、血药浓度、TG、TC、LDL-C和VLDL-C比较,差异具有统计学意义(均P<0.05);观察组与模型预测组药峰浓度、半衰期和药物浓度-时间曲线下面积比较,差异具有统计学意义(均P<0.05),但相对清除率、表观分布体积、达峰时间、血药浓度、TG、TC、LDL-C和VLDL-C比较,差异无统计学意义(P>0.05)。通过构建散点图观察发现,个体预测血药浓度值与实际值均匀分散在对角线两侧。3组不良反应发生率比较,差异有统计学意义(χ2=7.038,P<0.05)。结论:采用数学模型可预测阿托伐他汀治疗原发性高脂血症患者的最佳用药剂量,从而获得较好的临床效果,可应用于临床药物剂量的估算。 Objective: To explore the feasibility of using mathematical models to predict the dose-response relationship of atorvastatin on patients with primary hyperlipidemia. Methods: From January 2016 to December 2016, 92 patients with primary hyperlipidemia who received atorvastatin in Wangjing Hospital of Chinese Academy of Traditional Chinese Medicine were divided into control group, observation group and model group , Using mathematical models to predict the dose of atorvastatin and the treatment of primary hyperlipidemia effect. Results: The dose of atorvastatin in patients with primary hyperlipidemia was (29.16 ± 4.25) mg · d-1 and the steady-state dose was (19.45 ± 3.56) mg · d-1. The pharmacokinetic parameters, plasma concentration, triglyceride, total cholesterol, low density lipoprotein cholesterol and very low density lipoprotein cholesterol in the control group, observation group and the prediction group were significantly different (all P < 0.05). The differences of pharmacokinetic parameters, plasma concentration, TG, TC, LDL-C and VLDL-C between the control group and the observation group were statistically significant (all P <0.05); the pharmacokinetics TG, TC, LDL-C and VLDL-C, the difference was statistically significant (all P <0.05). The area under the curve of peak concentration, half-life and drug concentration- (P <0.05). There was no significant difference in relative clearance, apparent volume of distribution, peak time, plasma concentration, TG, TC, LDL-C and VLDL-C (P> 0.05). By constructing the scatter plot, it was found that the individual predicted plasma concentration and actual value were evenly distributed on both sides of the diagonal. The incidence of adverse reactions in the three groups, the difference was statistically significant (χ2 = 7.038, P <0.05). Conclusion: The optimal dose of atorvastatin in patients with primary hyperlipidemia can be predicted by mathematical model, so as to obtain better clinical effect and can be used in clinical drug dose estimation.
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