Quantifying and Adjusting for Confounding From Health-Seeking Behavior and Health Care Access in Observational Research.

IF 3.8 4区 医学 Q2 IMMUNOLOGY
Open Forum Infectious Diseases Pub Date : 2024-10-23 eCollection Date: 2024-10-01 DOI:10.1093/ofid/ofae598
Sophie Graham, Jemma L Walker, Nick Andrews, William J Hulme, Dorothea Nitsch, Edward P K Parker, Helen I McDonald
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Abstract

Background: Health-seeking behavior and health care access (HSB/HCA) are recognized confounders in many observational studies but are not directly measurable in electronic health records. We used proxy markers of HSB/HCA to quantify and adjust for confounding in observational studies of influenza and COVID-19 vaccine effectiveness (VE).

Methods: This cohort study used primary care data prelinked to secondary care and death data in England. We included individuals aged ≥66 years on 1 September 2019 and assessed influenza VE in the 2019-2020 season and early COVID-19 VE (December 2020-March 2021). VE was estimated with sequential adjustment for demographics, comorbidities, and 14 markers of HSB/HCA. Influenza vaccination in the 2019-2020 season was also considered a negative control exposure against COVID-19 before COVID-19 vaccine rollout.

Results: We included 1 991 284, 1 796 667, and 1 946 943 individuals in the influenza, COVID-19, and negative control exposure populations, respectively. Markers of HSB/HCA were positively correlated with influenza and COVID-19 vaccine uptake. For influenza, adjusting for HSB/HCA markers in addition to demographics and comorbidities increased VE against influenza-like illness from -1.5% (95% CI, -3.2% to .1%) to 7.1% (95% CI, 5.4%-8.7%) with a less apparent trend for more severe outcomes. For COVID-19, adjusting for HSB/HCA markers did not change VE estimates against infection or severe disease (eg, 2 doses of BNT162b2 against infection: 82.8% [95% CI, 78.4%-86.3%] to 83.1% [95% CI, 78.7%-86.5%]). Adjusting for HSB/HCA markers removed bias in the negative control exposure analysis (-7.5% [95% CI, -10.6% to -4.5%] vs -2.1% [95% CI, -6.0% to 1.7%] before vs after adjusting for HSB/HCA markers).

Conclusions: Markers of HSB/HCA can be used to quantify and account for confounding in observational vaccine studies.

在观察性研究中量化和调整求医行为与医疗服务获取的混杂因素。
背景:在许多观察性研究中,寻求健康的行为和获得医疗保健的机会(HSB/HCA)是公认的混杂因素,但在电子健康记录中却无法直接测量。我们使用 HSB/HCA 的替代标记来量化和调整流感和 COVID-19 疫苗有效性(VE)观察性研究中的混杂因素:这项队列研究使用了英格兰的初级保健数据,这些数据与二级保健和死亡数据预先关联。我们纳入了2019年9月1日年龄≥66岁的人,并评估了2019-2020年季节的流感VE和早期COVID-19 VE(2020年12月至2021年3月)。在对人口统计学、合并症和 14 个 HSB/HCA 标记进行连续调整后,对 VE 进行了估算。在COVID-19疫苗推出之前,2019-2020年流感季节的流感疫苗接种也被视为针对COVID-19的负对照暴露:我们在流感、COVID-19 和阴性对照暴露人群中分别纳入了 1 991 284 人、1 796 667 人和 1 946 943 人。HSB/HCA标记与流感疫苗和COVID-19疫苗接种率呈正相关。对于流感,除人口统计学和合并症外,调整 HSB/HCA 标记可将流感样疾病的 VE 从-1.5%(95% CI,-3.2% 至 .1%)增加到 7.1%(95% CI,5.4% 至 8.7%),且更严重后果的趋势不太明显。对于 COVID-19,调整 HSB/HCA 标志物不会改变针对感染或严重疾病的 VE 估计值(例如,2 剂 BNT162b2 针对感染的 VE 估计值:82.8% [95% CI, 78.4%-86.3%] 到 83.1% [95% CI, 78.7%-86.5%] )。调整HSB/HCA标记物消除了阴性对照暴露分析中的偏差(调整HSB/HCA标记物前后对比-7.5% [95% CI, -10.6% to -4.5%]对-2.1% [95% CI, -6.0% to 1.7%]):结论:HSB/HCA 标记可用于量化和考虑观察性疫苗研究中的混杂因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Open Forum Infectious Diseases
Open Forum Infectious Diseases Medicine-Neurology (clinical)
CiteScore
6.70
自引率
4.80%
发文量
630
审稿时长
9 weeks
期刊介绍: Open Forum Infectious Diseases provides a global forum for the publication of clinical, translational, and basic research findings in a fully open access, online journal environment. The journal reflects the broad diversity of the field of infectious diseases, and focuses on the intersection of biomedical science and clinical practice, with a particular emphasis on knowledge that holds the potential to improve patient care in populations around the world. Fully peer-reviewed, OFID supports the international community of infectious diseases experts by providing a venue for articles that further the understanding of all aspects of infectious diseases.
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