A Bayesian approach to sequential analysis in post‐licensure vaccine safety surveillance

Li, Rongxia; Stewart, Brock; Rose, Charles E.

doi:10.1002/pst.1991

Cited by 5 publications

(1 citation statement)

References 28 publications

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“…Despite potentially devastating consequences of COVID-19 infection in pregnant women and the availability of safe and efficacious (in non-pregnant populations) COVID-19 vaccination, there is limited published data describing the safety or efficacy of any COVID-19 vaccine in human pregnancy. Approval of vaccine use intended for pregnant or breastfeeding women rely on a critical review of observational studies, clinical case reports, registries, and clinical trials to ascertain if the vaccine is: (i) safe-no adverse pregnancy outcomes or potential harm to mother and/or fetus, (ii) efficacious-reduce morbidity in the pregnant woman and/or fetus [72][73][74][75][76][77][78][79][80][81]. These reviews are conducted through collaborative efforts between the World Health Organization (WHO), CDC, National Institutes of Health (NIH), ACIP, Task Force on Research Specific to Pregnant Women and Lactating Women, and Global Advisory Committee on Vaccine Safety, among others.…”

Section: Impact Of Covid-19 Vaccine In Pregnant Womenmentioning

confidence: 99%

COVID-19 Vaccine in Pregnant and Lactating Women: A Review of Existing Evidence and Practice Guidelines

Garg

Shekhar

Sheikh

et al. 2021

Infectious Disease Reports

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Coronavirus 2019 (COVID-19) has created a global pandemic that is devastating human lives, public healthcare systems, and global economies. Multiple effective and safe COVID-19 vaccines have been developed at an unprecedented speed due to the efforts of the scientific community, and collaboration between the federal government and pharmaceutical companies. However, the continued exclusion of pregnant and lactating women from the COVID anti-viral and vaccine trials has created the paradox of a lack of empirical evidence in a high-risk population. Based on the experience of similar prior vaccines, animal developmental and reproductive toxicology studies, and preliminary findings from human studies, various healthcare professional advisory committees (Advisory Committee on Immunization Practices, American College of Obstetricians and Gynecologists, Society for Maternal-Fetal Medicine, and Academy of Breastfeeding Medicine) have issued guidance supporting COVID-19 vaccination in pregnant and lactating women. In this article, we summarize the available data on the efficacy and safety profile of COVID-19 vaccination in pregnant and lactating women, review the challenges of vaccine hesitancy, and include recommendations for healthcare providers.

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Section: Impact Of Covid-19 Vaccine In Pregnant Womenmentioning

confidence: 99%

COVID-19 Vaccine in Pregnant and Lactating Women: A Review of Existing Evidence and Practice Guidelines

Garg

Shekhar

Sheikh

et al. 2021

Infectious Disease Reports

View full text Add to dashboard Cite

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Bayesian safety surveillance with adaptive bias correction

Bu,

Schuemie,

Nishimura

et al. 2023

Statistics in Medicine

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Postmarket safety surveillance is an integral part of mass vaccination programs. Typically relying on sequential analysis of real‐world health data as they accrue, safety surveillance is challenged by sequential multiple testing and by biases induced by residual confounding in observational data. The current standard approach based on the maximized sequential probability ratio test (MaxSPRT) fails to satisfactorily address these practical challenges and it remains a rigid framework that requires prespecification of the surveillance schedule. We develop an alternative Bayesian surveillance procedure that addresses both aforementioned challenges using a more flexible framework. To mitigate bias, we jointly analyze a large set of negative control outcomes that are adverse events with no known association with the vaccines in order to inform an empirical bias distribution, which we then incorporate into estimating the effect of vaccine exposure on the adverse event of interest through a Bayesian hierarchical model. To address multiple testing and improve on flexibility, at each analysis timepoint, we update a posterior probability in favor of the alternative hypothesis that vaccination induces higher risks of adverse events, and then use it for sequential detection of safety signals. Through an empirical evaluation using six US observational healthcare databases covering more than 360 million patients, we benchmark the proposed procedure against MaxSPRT on testing errors and estimation accuracy, under two epidemiological designs, the historical comparator and the self‐controlled case series. We demonstrate that our procedure substantially reduces Type 1 error rates, maintains high statistical power and fast signal detection, and provides considerably more accurate estimation than MaxSPRT. Given the extensiveness of the empirical study which yields more than 7 million sets of results, we present all results in a public R ShinyApp. As an effort to promote open science, we provide full implementation of our method in the open‐source R package EvidenceSynthesis.

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The coronavirus disease 2019 vaccine in pregnancy: risks, benefits, and recommendations

Stafford

Parchem

Sibai

2021

American Journal of Obstetrics and Gynecology

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The coronavirus disease 2019 has caused over 2 million deaths worldwide, with over 412,000 deaths reported in Unites States. To date, at least 57,786 pregnant women in the United States have been infected, and 71 pregnant women have died. Although pregnant women are at higher risk of severe coronavirus disease 2019erelated illness, clinical trials for the available vaccines excluded pregnant and lactating women. The safety and efficacy of the vaccines for pregnant women, the fetus, and the newborn remain unknown. A review of maternal and neonatal coronavirus disease 2019 morbidity and mortality data along with perinatal vaccine safety considerations are presented to assist providers with shared decision-making regarding vaccine administration for this group, including the healthcare worker who is pregnant, lactating, or considering pregnancy. The coronavirus disease 2019 vaccine should be offered to pregnant women after discussing the lack of safety data, with preferential administration for those at highest risk of severe infection, until safety and efficacy of these novel vaccines are validated.

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A Bayesian approach to sequential analysis in post‐licensure vaccine safety surveillance

Cited by 5 publications

References 28 publications

COVID-19 Vaccine in Pregnant and Lactating Women: A Review of Existing Evidence and Practice Guidelines

COVID-19 Vaccine in Pregnant and Lactating Women: A Review of Existing Evidence and Practice Guidelines

Bayesian safety surveillance with adaptive bias correction

The coronavirus disease 2019 vaccine in pregnancy: risks, benefits, and recommendations

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