University of Pittsburgh Department of Epidemiology, Suite 600 Schenley Place, 4420 Bayard St., Pittsburgh, PA 15260 USA.
University of Pittsburgh Department of Family Medicine, Suite 520 Schenley Place, 4420 Bayard St., Pittsburgh, PA 15260 USA.
Vaccine. 2021 Feb 22;39(8):1283-1289. doi: 10.1016/j.vaccine.2021.01.013. Epub 2021 Jan 21.
In some settings, research methods to determine influenza vaccine effectiveness (VE) may not be appropriate because of cost, time constraints, or other factors. Administrative database analysis of viral testing results and vaccination history may be a viable alternative. This study compared VE estimates from outpatient research and administrative databases.
Using the test-negative, case-control design, data for 2017-2018 and 2018-2019 influenza seasons were collected using: 1) consent, specimen collection, RT-PCR testing and vaccine verification using multiple methods; and 2) an administrative database of outpatients with a clinical respiratory viral panel combined with electronic immunization records. Odds ratios for likelihood of influenza infection by vaccination status were calculated using multivariable logistic regression. VE = (1 - aOR) × 100.
Research participants were significantly younger (P < 0.001), more often white (69% vs. 59%; P < 0.001) than non-white and less frequently enrolled through the emergency department (35% vs. 72%; P < 0.001) than administrative database participants. VE was significant against all influenza and influenza A in each season and both seasons combined (37-49%). Point estimate differences between methods were evident, with higher VE in the research database, but insignificant due to low sample sizes. When enrollment sites were separately analyzed, there were significant differences in VE estimates for all influenza (66% research vs. 46% administrative P < 0.001) and influenza A (67% research vs. 49% administrative; P < 0.001) in the emergency department.
The selection of the appropriate method for determining influenza vaccine effectiveness depends on many factors, including sample size, subgroups of interest, etc., suggesting that research estimates may be more generalizable. Other advantages of research databases for VE estimates include lack of clinician-related selection bias for testing and less misclassification of vaccination status. The advantages of the administrative databases are potentially shorter time to VE results and lower cost.
在某些情况下，由于成本、时间限制或其他因素，确定流感疫苗有效性（VE）的研究方法可能并不合适。对病毒检测结果和疫苗接种史的行政数据库分析可能是一种可行的替代方法。本研究比较了门诊研究和行政数据库的 VE 估计值。
使用病例对照设计，使用以下方法收集 2017-2018 年和 2018-2019 年流感季节的数据：1）使用多种方法获得同意、标本采集、RT-PCR 检测和疫苗验证；2）门诊临床呼吸道病毒组和电子免疫记录的行政数据库。使用多变量逻辑回归计算接种状态与流感感染可能性之间的优势比（OR）。VE=（1-aOR）×100。
研究参与者明显更年轻（P<0.001），更常为白人（69%比 59%；P<0.001），而非白人，较少通过急诊室入组（35%比 72%；P<0.001）。在每个季节和两个季节中，VE 对所有流感和 A 型流感均有显著意义（37-49%）。两种方法之间的点估计值差异明显，研究数据库中的 VE 更高，但由于样本量小，无统计学意义。当分别分析入组地点时，在所有流感（研究 66%比行政 46%，P<0.001）和 A 型流感（研究 67%比行政 49%，P<0.001）方面，VE 估计值存在显著差异。
确定流感疫苗有效性的适当方法的选择取决于许多因素，包括样本量、感兴趣的亚组等，这表明研究估计可能更具普遍性。研究数据库在 VE 估计方面的其他优势包括缺乏与临床医生相关的检测选择偏倚和疫苗接种状态的分类错误较少。行政数据库的优势在于 VE 结果的时间可能更短，成本可能更低。
