中国成年患者利奈唑胺治疗群体药动学研究

目的：通过回顾性分析来自恩泽医疗中心（集团）内3家医院利奈唑胺治疗患者的药物浓度监测（TDM）数据，建立中国成年患者利奈唑胺治疗群体药动学模型（PPK），为未来该群体患者利奈唑胺治疗单点谷浓度贝叶斯反馈预测个体化药动学参数，建立个体化给药方案，指导临床合理用药提供科学的实验支持。方法：从2016年3月至2018年12月收集了72例患者的血样，共监测了115个血清浓度。利用Kinetica软件中的逐步回归法研究药物清除率常数（K）和分布容积（Vd）与患者个体协变量（年龄、体质量、血常规、生化指标、合并用药等）之间的关系，并通过最大似然法和贝叶斯反馈法进行模型内部和外部验证。结果：最终模型分别为Vd=25.864－0.034×Fur（mg），K=0.324－0.000 3×Scr－0.003×Age+0.038×Burn。基础模型和最终模型拟合的Vd和K的群体典型值分别为29.719 L（5.32，52.36）、0.160 h-1（0.05，0.23）和25.322 L（2.50，52.51）、0.193 h-1（0.06，0.32）。基础模型和最终模型对应的外部验证平均绝对预测误差率分别为0.620（0.001，4.153）和0.588（0.014，3.942）。结论：本研究所建立的利奈唑胺最终PPK模型，能够良好地反映出中国成年患者的利奈唑胺PPK的变异特征；为提高治疗效果、减少不良反应以及实现个体化给药提供了重要的理论实验参考价值。

Population pharmacokinetics of Linezolid in Chinese adult infection patients#br#

AIM: The population pharmacokinetic model (PKK) of linezolid was constructed with the retrospective data of linezolid therapeutic drug monitoring from the 3 hospitals of ENZE medical center, which could be used to predict individualized pharmacokinetic parameters with Bayesian feedback method based on single point trough concentration and support scientific experimental method for rational drug use of linezolid in the future. METHODS: A total of 115 monitoring serum concentration data of 72 patients from Mar. 2016. to Dec. 2018 were included in this study. Stepwise regression method was used to screen the concomitant variable (age, weight, blood routine examination, biochemical index and drug combination etc.) for Vd and K by kinetica software. The internal and external validation were analyzed with maximum likihood method and Bayesian feedback. RESULTS: As the final model Vd=25.864－0.034×Fur(mg) shown, combination use of furosemide has a significant effect on Vd of linezolid. The level of age, Scr and the burn status of the patients have a significant effect on K of linezolid and the final model was K=0.324－0.0003×Scr－0.003×age +0.04×burn. Finally, the population mean value of Vd and K were 29.719 L(5.32, 52.36), 0.160 h-1 (0.05, 0.23) and 25.322 L (2.50, 52.51), 0.193 h-1 (0.06, 0.32) in basic model and final model. The mean absolute prediction error rate of external validation was 0.620 (0.001, 4.153) in basic model and 0.588 (0.014, 3.942) in final model. CONCLUSION: The final PPK model from the present study could well response the heterogeneous PPK characteristic of the patients from ENZE medical center, which could support scientific experiment method for improving the linezolid therapeutic effect and reducing adverse reaction rate.