Meah Sabir, Shi Xu, Fritsche Lars G, Salvatore Maxwell, Wagner Abram, Martin Emily T, Mukherjee Bhramar
Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
Center for Precision Health Data Science, University of Michigan, Ann Arbor, MI 48109, USA.
medRxiv. 2023 Jun 28:2023.06.22.23291692. doi: 10.1101/2023.06.22.23291692.
Observational vaccine effectiveness (VE) studies based on real-world data are a crucial supplement to initial randomized clinical trials of Coronavirus Disease 2019 (COVID-19) vaccines. However, there exists substantial heterogeneity in study designs and statistical methods for estimating VE. The impact of such heterogeneity on VE estimates is not clear.
We conducted a two-step literature review of booster VE: a literature search for first or second monovalent boosters on January 1, 2023, and a rapid search for bivalent boosters on March 28, 2023. For each study identified, study design, methods, and VE estimates for infection, hospitalization, and/or death were extracted and summarized via forest plots. We then applied methods identified in the literature to a single dataset from Michigan Medicine (MM), providing a comparison of the impact of different statistical methodologies on the same dataset.
We identified 53 studies estimating VE of the first booster, 16 for the second booster. Of these studies, 2 were case-control, 17 were test-negative, and 50 were cohort studies. Together, they included nearly 130 million people worldwide. VE for all outcomes was very high (around 90%) in earlier studies (i.e., in 2021), but became attenuated and more heterogeneous over time (around 40%-50% for infection, 60%-90% for hospitalization, and 50%-90% for death). VE compared to the previous dose was lower for the second booster (10-30% for infection, 30-60% against hospitalization, and 50-90% against death). We also identified 11 bivalent booster studies including over 20 million people. Early studies of the bivalent booster showed increased effectiveness compared to the monovalent booster (VE around 50-80% for hospitalization and death).Our primary analysis with MM data using a cohort design included 186,495 individuals overall (including 153,811 boosted and 32,684 with only a primary series vaccination), and a secondary test-negative design included 65,992 individuals tested for SARS-CoV-2. When different statistical designs and methods were applied to MM data, VE estimates for hospitalization and death were robust to analytic choices, with test-negative designs leading to narrower confidence intervals. Adjusting either for the propensity of getting boosted or directly adjusting for covariates reduced the heterogeneity across VE estimates for the infection outcome.
While the advantage of the second monovalent booster is not obvious from the literature review, the first monovalent booster and the bivalent booster appear to offer strong protection against severe COVID-19. Based on both the literature view and data analysis, VE analyses with a severe disease outcome (hospitalization, ICU admission, or death) appear to be more robust to design and analytic choices than an infection endpoint. Test-negative designs can extend to severe disease outcomes and may offer advantages in statistical efficiency when used properly.
基于真实世界数据的观察性疫苗有效性（VE）研究是2019冠状病毒病（COVID-19）疫苗初始随机临床试验的重要补充。然而，在估计VE的研究设计和统计方法方面存在很大的异质性。这种异质性对VE估计的影响尚不清楚。
我们对加强针的VE进行了两步文献综述：2023年1月1日对单价第一剂或第二剂加强针进行文献检索，2023年3月28日对双价加强针进行快速检索。对于每项纳入研究，提取其研究设计、方法以及感染、住院和/或死亡的VE估计值，并通过森林图进行总结。然后，我们将文献中确定的方法应用于密歇根大学医学中心（MM）的单个数据集，比较不同统计方法对同一数据集的影响。
我们确定了53项估计第一剂加强针VE的研究，16项估计第二剂加强针VE的研究。在这些研究中，2项为病例对照研究，17项为检测阴性设计，50项为队列研究。这些研究总共纳入了全球近1.3亿人。在早期研究（即2021年）中，所有结局的VE都非常高（约90%），但随着时间的推移，VE减弱且异质性增加（感染约40%-50%，住院约60%-90%，死亡约50%-90%）。与前一剂相比，第二剂加强针的VE较低（感染为10%-30%，住院为30%-60%，死亡为50%-90%）。我们还确定了11项双价加强针研究，纳入了超过2000万人。双价加强针的早期研究显示，与单价加强针相比有效性有所提高（住院和死亡的VE约为50%-80%）。我们使用队列设计对MM数据进行的主要分析总共纳入了186495人（包括153811名接种加强针者和32684名仅接种了初始系列疫苗者），二级检测阴性设计纳入了65992名接受SARS-CoV-2检测的人。当将不同的统计设计和方法应用于MM数据时，住院和死亡的VE估计值对分析选择具有稳健性，检测阴性设计导致的置信区间更窄。对加强针接种倾向进行调整或直接对协变量进行调整，可减少感染结局VE估计值之间的异质性。
虽然从文献综述来看，第二剂单价加强针的优势不明显，但第一剂单价加强针和双价加强针似乎对重症COVID-19提供了强有力的保护。基于文献综述和数据分析，针对严重疾病结局（住院、入住重症监护病房或死亡）的VE分析似乎比感染终点对设计和分析选择更具稳健性。检测阴性设计可扩展到严重疾病结局，并且在正确使用时可能在统计效率方面具有优势。
