Westreich Daniel, Hudgens Michael G
Am J Epidemiol. 2016 Sep 1;184(5):354-6. doi: 10.1093/aje/kww063.
In this issue of the Journal, Sullivan et al. (Am J Epidemiol. 2016;184(5):345-353) carefully examine the theoretical justification for use of the test-negative design, a common observational study design, in assessing the effectiveness of influenza vaccination. Using modern causal inference methods (in particular, directed acyclic graphs), they describe different threats to the validity of inferences drawn about the effect of vaccination from test-negative design studies. These threats include confounding, selection bias, and measurement error in either the exposure or the outcome. While confounding and measurement error are common in observational studies, the potential for selection bias inherent in the test-negative design brings into question the validity of inferences drawn from such studies.
在本期《期刊》中，沙利文等人（《美国流行病学杂志》。2016年；184(5):345 - 353）仔细研究了使用检测阴性设计（一种常见的观察性研究设计）来评估流感疫苗接种效果的理论依据。他们运用现代因果推断方法（特别是有向无环图），描述了从检测阴性设计研究中得出的关于疫苗接种效果的推断有效性所面临的不同威胁。这些威胁包括混杂、选择偏倚以及暴露或结局中的测量误差。虽然混杂和测量误差在观察性研究中很常见，但检测阴性设计中固有的选择偏倚可能性使得从此类研究得出的推断的有效性受到质疑。
