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疫苗真实世界研究中的统计方法

Statistical Methods of Real World Study for Licensed Vaccines

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【作者】 戚洋洋蒋志伟王永吉夏结来汪萱怡

【Author】 QI Yang-yang;JIANG Zhi-wei;WANG Yong-ji;XIA Jie-lai;WANG Xuan-yi;Shanghai Institute of Infectious Disease and Biosecurity;Beijing Key Tech Statistical Consulting Co.,Ltd.;Xijing Hospital;Key Laboratory of Medical Molecular Virology of MoE & NHC,Fudan University;Institutes of Biomedical Sciences,Fudan University;Children’s Hospital,Fudan University;

【通讯作者】 汪萱怡;

【机构】 上海市重大传染病和生物安全研究院北京康特瑞科统计科技有限责任公司西京医院复旦大学教育部/卫健委医学分子病毒学重点实验室复旦大学生物医学研究院复旦大学附属儿科医院

【摘要】 随机对照盲法临床试验用于评价疫苗安全性与有效性是公认的金标准,但由于其设计上的严苛,使得疫苗上市后,在大规模应用场景下的疫苗真实保护效果与临床试验获得的保护效力往往存在偏差,疫苗真实世界研究在此基础上被提出。新冠病毒疫苗真实世界研究被大量报道,其结果被各国采用,及时优化疫苗免疫策略。本文概括了常见的疫苗真实世界研究设计,并着重介绍了近些年发展出来的解决真实世界研究中混杂偏倚的统计方法 :倾向评分和工具变量。

【Abstract】 Randomized controlled double-blind clinical trials are widely recognized as the gold standard for evaluating the safety and efficacy of vaccines. However, due to their rigorous design, a deviation often exists between the protection efficacy obtained in large-scale vaccine applications in real-world scenarios and the efficacy observed in clinical trials. Real world studies of vaccines have been proposed to address this issue. The real world study on COVID-19 vaccines, in particular, has been widely reported, and its results have been adopted by various countries to optimize vaccine immunization strategies. This article summarizes common designs for real world vaccine studies and focuses on recent statistical methods developed to address confounding bias in real world studies: propensity score and instrumental variable.

  • 【文献出处】 中国食品药品监管 ,China Food & Drug Administration Magazine , 编辑部邮箱 ,2023年12期
  • 【分类号】R186
  • 【下载频次】20
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