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目的:建立国人紫杉醇(paclitaxel,PTX)群体药动学(population pharmacokinetic,PPK)模型,为制定个体化给药方案提供理论支持。方法:收集138例接受紫杉醇治疗的肿瘤患者(建模组105例,验证组33例)210个血样,HPLC法测定紫杉醇血药浓度,PCR-RFLP法检测MDR1 C3435T。应用非线性混合效应模型(NONMEM)法,考察MDR1 C3435T基因多态性、合并用药及病理生理因素对紫杉醇药动学参数的影响,建立紫杉醇PPK模型。对模型进行拟合优度诊断、自举法(Bootstrap)内部验证,正态预测分布误差法(NPDE)及外部验证考察模型预测能力。结果:紫杉醇清除率(CL)和表观分布容积(Vd)的群体典型值分别为64.7 L·h~(-1)和1 240 L,患者内生肌酐清除率(CLcr)和给药速率(RATE)显著影响紫杉醇清除率。最终模型Bootstrap法验证结果与模型计算值相符,拟合优度、准确度及精密度均优于最简模型。结论:紫杉醇PPK最终模型稳定、有效,可结合Bayesian反馈法为临床优化给药方案提供科学依据。
OBJECTIVE: To establish a population pharmacokinetic (PPK) model of paclitaxel (PTX) in China and to provide theoretical support for the development of individualized drug delivery schemes. METHODS: Totally 210 blood samples were collected from 138 cancer patients treated with paclitaxel (105 in the model group and 33 in the validation group). Plasma concentrations of paclitaxel were determined by HPLC and MDR1 C3435T by PCR-RFLP. The nonlinear mixed effect model (NONMEM) method was used to investigate the effect of MDR1 C3435T gene polymorphism, combination therapy and pathophysiological factors on the pharmacokinetics parameters of paclitaxel, and the PPK model of paclitaxel was established. The goodness of fit of the model was diagnosed, Bootstrap internal verification, normal predictive distribution error method (NPDE) and external validation were used to evaluate the predictive ability of the model. Results: The typical values of CL and Vd were 64.7 L · h ~ (-1) and 1240 L, respectively. The patients’ endogenous creatinine clearance rate (CLcr) and administration rate RATE) significantly affected paclitaxel clearance. The result of Bootstrap method is in good agreement with the calculated value of the model. The goodness of fit, accuracy and precision are better than the simplest model. Conclusion: The final model of paclitaxel PPK is stable and effective, which can provide a scientific basis for the clinical optimization of drug delivery scheme by Bayesian feedback method.