Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
Vaccine. 2013 Jun 26;31(30):3104-9. doi: 10.1016/j.vaccine.2013.04.026. Epub 2013 Apr 23.
A modification to the case-control study design has become popular to assess vaccine effectiveness (VE) against viral infections. Subjects with symptomatic illness seeking medical care are tested by a highly specific polymerase chain reaction (PCR) assay for the detection of the infection of interest. Cases are subjects testing positive for the virus; those testing negative represent the comparison group. Influenza and rotavirus VE studies using this design are often termed "test-negative case-control" studies, but this design has not been formally described or evaluated. We explicitly state several assumptions of the design and examine the conditions under which VE estimates derived with it are valid and unbiased.
We derived mathematical expressions for VE estimators obtained using this design and examined their statistical properties. We used simulation methods to test the validity of the estimators and illustrate their performance using an influenza VE study as an example.
Because the marginal ratio of cases to non-cases is unknown during enrollment, this design is not a traditional case-control study; we suggest the name "case test-negative" design. Under sets of increasingly general assumptions, we found that the case test-negative design can provide unbiased VE estimates. However, differences in health care-seeking behavior among cases and non-cases by vaccine status, strong viral interference, or modification of the probability of symptomatic illness by vaccine status can bias VE estimates.
Vaccine effectiveness estimates derived from case test-negative studies are valid and unbiased under a wide range of assumptions. However, if vaccinated cases are less severely ill and seek care less frequently than unvaccinated cases, then an appropriate adjustment for illness severity is required to avoid bias in effectiveness estimates. Viral interference will lead to a non-trivial bias in the vaccine effectiveness estimate from case test-negative studies only when incidence of influenza is extremely high and duration of transient non-specific immunity is long.
一种修改后的病例对照研究设计已广泛用于评估针对病毒感染的疫苗效力（VE）。有症状疾病的受试者通过高度特异性聚合酶链反应（PCR）检测来检测感兴趣的感染。病例是检测出病毒呈阳性的受试者；那些检测结果呈阴性的则代表对照组。使用这种设计的流感和轮状病毒 VE 研究通常被称为“阴性病例对照”研究，但这种设计尚未得到正式描述或评估。我们明确陈述了该设计的几个假设，并研究了使用该设计得出的 VE 估计值有效的和无偏的条件。
我们推导出了使用该设计获得的 VE 估计量的数学表达式，并研究了它们的统计性质。我们使用模拟方法来检验估计量的有效性，并以流感 VE 研究为例来说明它们的性能。
由于在入组时不知道病例与非病例的边缘比，因此该设计不是传统的病例对照研究；我们建议将其命名为“病例检测阴性”设计。在越来越普遍的假设下，我们发现病例检测阴性设计可以提供无偏的 VE 估计值。但是，疫苗接种状态下病例和非病例之间的医疗保健寻求行为差异、强病毒干扰或疫苗接种状态下症状性疾病发生概率的改变都可能导致 VE 估计值出现偏差。
在广泛的假设下，从病例检测阴性研究中得出的疫苗效力估计值是有效的且无偏的。然而，如果接种疫苗的病例比未接种疫苗的病例病情较轻且不太频繁地寻求治疗，那么为了避免对效力估计的偏差，需要对疾病严重程度进行适当的调整。只有当流感的发病率极高且短暂的非特异性免疫持续时间较长时，病例检测阴性研究中的病毒干扰才会导致疫苗效力估计值出现实质性偏差。
