评估和减少流感和 COVID-19 疫苗有效性分析中的偏差 - IVY 网络,2022 年 9 月 1 日至 2023 年 3 月 30 日。

IF 4.5 3区 医学 Q2 IMMUNOLOGY Vaccine Pub Date : 2024-11-07 DOI:10.1016/j.vaccine.2024.126492
Nathaniel M. Lewis , Elizabeth J. Harker , Aleda Leis , Yuwei Zhu , H. Keipp Talbot , Carlos G. Grijalva , Natasha Halasa , James D. Chappell , Cassandra A. Johnson , Todd W. Rice , Jonathan D. Casey , Adam S. Lauring , Manjusha Gaglani , Shekhar Ghamande , Cristie Columbus , Jay S. Steingrub , Nathan I. Shapiro , Abhijit Duggal , Jamie Felzer , Matthew E. Prekker , Emily T. Martin
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引用次数: 0

摘要

背景:在疫苗有效性(VE)的阴性试验研究中,将患有可通过疫苗预防的呼吸道病原体的患者纳入相关病原体的对照组可能会导致VE估计值向下偏移:美国的一个多中心哨点监测网络在 2022 年 9 月 1 日至 2023 年 3 月 31 日期间对因急性呼吸道疾病住院的成人进行了前瞻性登记。我们根据以下因素评估了针对流感相关住院和 COVID-19 相关住院的 VE 估计值的偏差:在 VE 对照中纳入与排除共同流行病毒患者;观察针对共同流行病毒(而非相关病毒)的 VE,未调整和调整针对相关病毒的疫苗接种;观察流感或 COVID-19 与呼吸道合胞病毒(RSV)的假结果:当对照组中包括COVID-19患者时,流感相关住院治疗的总体VE降低了6个百分点;当对照组中包括流感患者时,COVID-19相关住院治疗的总体VE降低了2个百分点。针对共循环病毒和RSV假性结果的VE分析表明,向下偏差主要归因于不同病原体之间疫苗接种状况的相关性,但也可能归因于VE模型中其他残留混杂因素:结论:在对相关病原体进行 VE 分析时,将呼吸道病原体混杂病例排除在对照组之外可减少向下偏倚。这项真实世界的分析表明,这种排除是一种有用的减少偏差策略,尤其是在测量流感 VE 时,因为对照组中 COVID-19 病例的比例很高。
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Assessment and mitigation of bias in influenza and COVID-19 vaccine effectiveness analyses — IVY Network, September 1, 2022–March 30, 2023

Background

In test-negative studies of vaccine effectiveness (VE), including patients with co-circulating, vaccine-preventable, respiratory pathogens in the control group for the pathogen of interest can introduce a downward bias on VE estimates.

Methods

A multicenter sentinel surveillance network in the US prospectively enrolled adults hospitalized with acute respiratory illness from September 1, 2022–March 31, 2023. We evaluated bias in estimates of VE against influenza–associated and COVID-19–associated hospitalization based on: inclusion vs exclusion of patients with a co-circulating virus among VE controls; observance of VE against the co-circulating virus (rather than the virus of interest), unadjusted and adjusted for vaccination against the virus of interest; and observance of influenza or COVID-19 against a sham outcome of respiratory syncytial virus (RSV).

Results

Overall VE against influenza–associated hospitalizations was 6 percentage points lower when patients with COVID-19 were included in the control group, and overall VE against COVID-19–associated hospitalizations was 2 percentage points lower when patients with influenza were included in the control group. Analyses of VE against the co-circulating virus and against the sham outcome of RSV showed that downward bias was largely attributable the correlation of vaccination status across pathogens, but also potentially attributable to other sources of residual confounding in VE models.

Conclusion

Excluding cases of confounding respiratory pathogens from the control group in VE analysis for a pathogen of interest can reduce downward bias. This real-world analysis demonstrates that such exclusion is a helpful bias mitigation strategy, especially for measuring influenza VE, which included a high proportion of COVID-19 cases among controls.
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来源期刊
Vaccine
Vaccine 医学-免疫学
CiteScore
8.70
自引率
5.50%
发文量
992
审稿时长
131 days
期刊介绍: Vaccine is unique in publishing the highest quality science across all disciplines relevant to the field of vaccinology - all original article submissions across basic and clinical research, vaccine manufacturing, history, public policy, behavioral science and ethics, social sciences, safety, and many other related areas are welcomed. The submission categories as given in the Guide for Authors indicate where we receive the most papers. Papers outside these major areas are also welcome and authors are encouraged to contact us with specific questions.
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