Observational studies and the difficult quest for causality: lessons from vaccine effectiveness and impact studies
Observational studies and the difficult quest for causality: lessons from vaccine effectiveness and impact studies
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DOI：
10.1093/ije/dyw124
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发表时间：
2016-12-01
影响因子：
7.7
通讯作者：
Simonsen, Lone
中科院分区：
文献类型：
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作者：
Lipsitch, Marc;Jha, Ayan;Simonsen, Lone
尽管随机安慰剂对照试验（RCT）对于在许可时确定疫苗的有效性至关重要，但关于疫苗有效性（VE）的重要遗留问题（这里用于包括个人水平的测量和疫苗计划的人群影响）只有在疫苗投入使用后才能从观察性研究中得到答案。然而，这类研究本身就存在偏倚风险。使用因果框架并举例说明，我们回顾了在三个主要类别的观察性研究设计中发现和避免混淆和选择偏差的新方法：队列研究、病例对照研究和生态研究。对流感病毒的研究，特别是对老年人的研究，很好地证明了发现和减少这种偏见的挑战，因此我们使用流感病毒作为一个运行的例子。我们对经常被视为“生态学”的时间趋势研究进行了新的审视。这样的设计是唯一的观察性研究设计，可以衡量疫苗接种规划的总体效果[间接（群体）和直接效果]，而且实际上已经是目前使用的几种疫苗的证据基础的重要组成部分。尽管在更稳健的观察性研究设计方面取得了巨大的进步，但在评估从观察性研究中获得稳健、公正结果的最佳实践方面仍存在挑战。这对于评价国家和全球疫苗规划的效力至关重要。
Although randomized placebo-controlled trials (RCT) are critical to establish efficacy of vaccines at the time of licensure, important remaining questions about vaccine effectiveness (VE)-used here to include individual-level measures and population-wide impact of vaccine programmes-can only be answered once the vaccine is in use, from observational studies. However, such studies are inherently at risk for bias. Using a causal framework and illustrating with examples, we review newer approaches to detecting and avoiding confounding and selection bias in three major classes of observational study design: cohort, case-control and ecological studies. Studies of influenza VE, especially in seniors, are an excellent demonstration of the challenges of detecting and reducing such bias, and so we use influenza VE as a running example. We take a fresh look at the time-trend studies often dismissed as 'ecological'. Such designs are the only observational study design that can measure the overall effect of a vaccination programme [indirect (herd) as well as direct effects], and are in fact already an important part of the evidence base for several vaccines currently in use. Despite the great strides towards more robust observational study designs, challenges lie ahead for evaluating best practices for achieving robust unbiased results from observational studies. This is critical for evaluation of national and global vaccine programme effectiveness.