背景:确定疫苗有效性(VE)是研究每种新疫苗的重要组成部分。测试阴性病例对照(TNCC)研究最近已用于确定VE。然而,来自TNCC设计的估计VE取决于测试灵敏度和特异性.在这里,提出了一种校正TNCC研究得出的VE值的方法。
方法:提出了一种分析方法,用于根据所使用的诊断测试的灵敏度和特异性来计算校正的VE。为了展示所提出方法的应用,提出了一项假想的TNCC研究。在这项计算机模拟研究中,10万名涉及COVID-19样疾病医疗系统的人接受了诊断测试,敏感性为0.6、0.8和1.0,特异性为0.85至1.00。疫苗接种覆盖率为60%,未接种组COVID-19的发病率为0.05,并且假设真实的VE为0.70。在这个模拟中,发病率为0.30的COVID-19样疾病也可能影响所有研究人群,无论他们的疫苗接种状况如何。
结果:观察到的VE范围从0.11(计算测试灵敏度为0.60和特异性为0.85)到0.71(计算测试灵敏度和特异性为1.0)。从所提出的方法得出的平均计算校正VE为0.71(标准偏差为0.02)。
结论:从TNCC研究中观察到的VE可以很容易地校正。无论研究中使用的诊断测试灵敏度和特异性如何,都可以计算VE的可接受估计值。
BACKGROUND: Determining the vaccine effectiveness (VE) is an important part of studying every new vaccine. Test-negative
case-control (TNCC) studies have recently been used to determine the VE. However, the estimated VE derived from a TNCC design depends on the test sensitivity and specificity. Herein, a method for correction of the value of VE derived from a TNCC study is presented.
METHODS: An analytical method is presented to compute the corrected VE based on the sensitivity and specificity of the diagnostic test utilized. To show the application of the method proposed, a hypothetical TNCC study is presented. In this in silico study, 100 000 individuals referring to a healthcare system for COVID-19-like illness were tested with diagnostic tests with sensitivities of 0.6, 0.8, and 1.0, and specificities ranging from 0.85 to 1.00. A vaccination coverage of 60%, an attack rate of 0.05 for COVID-19 in unvaccinated group, and a true VE of 0.70, were assumed. In this simulation, a COVID-19-like illness with an attack rate of 0.30 could also affect all the studied population regardless of their vaccination status.
RESULTS: The observed VE ranged from 0.11 (computed for a test sensitivity of 0.60 and specificity of 0.85) to 0.71 (computed for a test sensitivity and specificity of 1.0). The mean computed corrected VE derived from the proposed method was 0.71 (the standard deviation of 0.02).
CONCLUSIONS: The observed VE derived from TNCC studies can be corrected easily. An acceptable estimate for VE can be computed regardless of the diagnostic test sensitivity and specificity used in the study.