替加环素的群体药动学研究进展

Population Pharmacokinetics of Tigecycline

目的替加环素是首个甘氨酰环素类抗菌药物,具有超广谱的抗菌活性。近年来,替加环素的群体药动学研究不断被报道,本文旨在全面总结替加环素的群体药动学模型特征,为替加环素的个体化用药提供理论依据。方法本文通过系统性检索PubMed、Embase、中国知网(CNKI)、万方和维普等数据库,收集从建库到2020年5月发表的群体药物动力学模型。结果本文共纳入6项研究,包含了健康志愿者、皮肤软组织感染、腹腔感染、社区获得性肺炎、医院获得性肺炎、感染性休克等各类男性和女性人群,覆盖年龄18~92岁,替加环素剂量为12.5~300 mg,给药时间为0.5~4 h。所有研究中均使用一级线性消除,二室模型。最常见的协变量是体重或与体重相关的变量,及肌酐清除率,其次还包括性别、剂量和胆红素。没有研究使用外部验证对模型进行评估。结论尽管这些研究都包含了几个协变量,但药动学参数间仍存在较大的变异,新的或潜在的协变量需进一步进行研究。未来可以通过在一个设计良好的群体药动学模型中加入其他的潜在变量,如遗传多态性、代谢因素和伴随的药物进行改进。此外,后续研究也可对已经发表的模型进行外部验证,比较不同模型间的预测性能。

OBJECTIVE To comprehensively summarize the population pharmacokinetic models for tigecycline,and to determine which covariates have been identified and which remain to be explored.METHODS A systematic review was performed by searching PubMed,Embase,CNKI,Wangfang and VIP databases from inception to May 2020.RESULTS Six studies were included in this review,containing healthy volunteers,male and female populations with skin and soft tissue infections,abdominal cavity infections,community-acquired pneumonia,hospital-acquired pneumonia and septic shock,covering the age of 18-92 years old.The dose of tigecycline was 12.5-300 mg,and the time of administration was 0.5-4 h.Tigecycline pharmacokinetics was described as two-compartment with first-order elimination in all studies.Weight or weight-related variables,creatinine clearance,gender,dosage and bilirubin were found to be the most common identified covariates affecting these parameters.No external validation was performed in all studies.CONCLUSION Large pharmacokinetic variability remains despite the inclusion of several covariates.This can be improved by including other potential factors such as genetic polymorphisms,metabolic factors,and significant drug-drug interactions in a well-designed population pharmacokinetic model in the future,taking into account the incorporation of larger sample size and more stringent sampling strategy.External validation should also be performed to the previously published models to compare their predictive performances.