Evaluation of potential adverse events following COVID-19 mRNA vaccination among adults aged 65 years and older: Two self-controlled studies in the U.S

Risk of major adverse cerebro-cardiovascular events following BNT162b2, CoronaVac, and ChAdOx1 vaccination and SARS-CoV-2 infection: A self-controlled case-series study

OBJECTIVE

To assess the potential risk of major adverse cerebro-cardiovascular events (MACCE) associated with COVID-19 vaccination and SARS-CoV-2 infection.

METHODS

This self-controlled case series study used nationwide health database from Malaysia. The study included individuals aged ≥18 years who were hospitalised between 24 February 2021 and 30 June 2022. Outcomes were composite of MACCE: stroke, acute ischaemic heart disease, and cardiovascular death. Exposures were COVID-19 vaccination and SARS-CoV-2 infection. The risk period was day 1 to day 21 following exposure. Conditional Poisson regression model was used to estimate the incidence rate ratios (IRRs) and 95 % confidence interval (CI) comparing the outcomes in the risk and control periods.

RESULTS

The risk of MACCE within 21 days after vaccination per 100,000 doses administered were 12.0 (95% CI 11.9-12.1) (BNT162b2), 9.2 (95% CI 9.1-9.3) (CoronaVac), and 6.8 (95% CI 6.6-7.0) (ChAdOx1). The incidence rate ratios showed no increased risk of MACCE associated with the first, second, or third doses of BNT162b2, CoronaVac, and ChAdOx1 vaccines for individuals without prior cardiovascular disease (CVD). This finding was consistent for individuals with CVD. Vaccine booster dose, whether in a homologous or heterologous schedule, did not show increased risk of MACCE. Analysis by ethnic groups detected a slightly elevated risk of MACCE in Indian after the first dose of ChAdOx1 (IRR 1.64; 95% CI 1.08-2.48) in those without CVD. No significant association were observed in other subgroup analyses. SARS-CoV-2 infection was associated with significantly increased risk of MACCE in individuals without CVD (IRR 3.54; 95% CI 3.32-3.76) and with CVD (IRR 1.98; 95% CI 1.61-2.34).

CONCLUSIONS

Our findings support the favourable safety profile of these COVID-19 vaccines and indicate that the overall benefit-risk ratio of the COVID-19 vaccines remains positive.

Risk for Facial Palsy after COVID-19 Vaccination, South Korea, 2021-2022

We conducted a self-controlled case series study to investigate the association between COVID-19 vaccination and facial palsy (FP) in South Korea. We used a large immunization registry linked with the national health information database. We included 44,564,345 patients >18 years of age who received >1 dose of COVID-19 vaccine (BNT162b2, mRNA-1273, ChAdOx1 nCoV-19, or Ad.26.COV2.S) and had an FP diagnosis and corticosteroid prescription within 240 days postvaccination. We compared FP incidence in a risk window (days 1-28) with a control window (the remainder of the 240-day observation period, excluding any risk windows). We found 5,211 patients experienced FP within the risk window and 10,531 experienced FP within the control window. FP risk increased within 28 days postvaccination, primarily after first and second doses and was observed for both mRNA and viral vaccines. Clinicians should carefully assess the FP risk-benefit profile associated with the COVID-19 vaccines and monitor neurologic signs after vaccination.

COVID-19 Vaccine Safety Technical (VaST) Work Group: Enhancing vaccine safety monitoring during the pandemic

During the COVID-19 pandemic, candidate COVID-19 vaccines were being developed for potential use in the United States on an unprecedented, accelerated schedule. It was anticipated that once available, under U.S. Food and Drug Administration (FDA) Emergency Use Authorization (EUA) or FDA approval, COVID-19 vaccines would be broadly used and potentially administered to millions of individuals in a short period of time. Intensive monitoring in the post-EUA/licensure period would be necessary for timely detection and assessment of potential safety concerns. To address this, the Centers for Disease Control and Prevention (CDC) convened an Advisory Committee on Immunization Practices (ACIP) work group focused solely on COVID-19 vaccine safety, consisting of independent vaccine safety experts and representatives from federal agencies - the ACIP COVID-19 Vaccine Safety Technical Work Group (VaST). This report provides an overview of the organization and activities of VaST, summarizes data reviewed as part of the comprehensive effort to monitor vaccine safety during the COVID-19 pandemic, and highlights selected actions taken by CDC, ACIP, and FDA in response to accumulating post-authorization safety data. VaST convened regular meetings over the course of 29 months, from November 2020 through April 2023; through March 2023 FDA issued EUAs for six COVID-19 vaccines from four different manufacturers and subsequently licensed two of these COVID-19 vaccines. The independent vaccine safety experts collaborated with federal agencies to ensure timely assessment of vaccine safety data during this time. VaST worked closely with the ACIP COVID-19 Vaccines Work Group; that work group used safety data and VaST's assessments for benefit-risk assessments and guidance for COVID-19 vaccination policy. Safety topics reviewed by VaST included those identified in safety monitoring systems and other topics of scientific or public interest. VaST provided guidance to CDC's COVID-19 vaccine safety monitoring efforts, provided a forum for review of data from several U.S. government vaccine safety systems, and assured that a diverse group of scientists and clinicians, external to the federal government, promptly reviewed vaccine safety data. In the event of a future pandemic or other biological public health emergency, the VaST model could be used to strengthen vaccine safety monitoring, enhance public confidence, and increase transparency through incorporation of independent, non-government safety experts into the monitoring process, and through strong collaboration among federal and other partners.

Development of Interoperable Computable Phenotype Algorithms for Adverse Events of Special Interest to Be Used for Biologics Safety Surveillance: Validation Study

BACKGROUND

Adverse events associated with vaccination have been evaluated by epidemiological studies and more recently have gained additional attention with the emergency use authorization of several COVID-19 vaccines. As part of its responsibility to conduct postmarket surveillance, the US Food and Drug Administration continues to monitor several adverse events of special interest (AESIs) to ensure vaccine safety, including for COVID-19.

OBJECTIVE

This study is part of the Biologics Effectiveness and Safety Initiative, which aims to improve the Food and Drug Administration's postmarket surveillance capabilities while minimizing public burden. This study aimed to enhance active surveillance efforts through a rules-based, computable phenotype algorithm to identify 5 AESIs being monitored by the Center for Disease Control and Prevention for COVID-19 or other vaccines: anaphylaxis, Guillain-Barré syndrome, myocarditis/pericarditis, thrombosis with thrombocytopenia syndrome, and febrile seizure. This study examined whether these phenotypes have sufficiently high positive predictive value (PPV) to ensure that the cases selected for surveillance are reasonably likely to be a postbiologic adverse event. This allows patient privacy, and security concerns for the data sharing of patients who had nonadverse events can be properly accounted for when evaluating the cost-benefit aspect of our approach.

METHODS

AESI phenotype algorithms were developed to apply to electronic health record data at health provider organizations across the country by querying for standard and interoperable codes. The codes queried in the rules represent symptoms, diagnoses, or treatments of the AESI sourced from published case definitions and input from clinicians. To validate the performance of the algorithms, we applied them to electronic health record data from a US academic health system and provided a sample of cases for clinicians to evaluate. Performance was assessed using PPV.

RESULTS

With a PPV of 93.3%, our anaphylaxis algorithm performed the best. The PPVs for our febrile seizure, myocarditis/pericarditis, thrombocytopenia syndrome, and Guillain-Barré syndrome algorithms were 89%, 83.5%, 70.2%, and 47.2%, respectively.

CONCLUSIONS

Given our algorithm design and performance, our results support continued research into using interoperable algorithms for widespread AESI postmarket detection.