A broad assessment of covid-19 vaccine safety using tree-based data-mining in the vaccine safety datalink.

BACKGROUND: Except for spontaneous reporting systems, vaccine safety monitoring generally involves pre-specifying health outcomes and post-vaccination risk windows of concern. Instead, we used tree-based data-mining to look more broadly for possible adverse events after Pfizer-BioNTech, Moderna, and Janssen COVID-19 vaccination. METHODS: Vaccine Safety Datalink enrollees receiving ≥1 dose of COVID-19 vaccine in 2020-2021 were followed for 70 days after Pfizer-BioNTech or Moderna and 56 days after Janssen vaccination. Incident diagnoses in inpatient or emergency department settings were analyzed for clustering within both the hierarchical ICD-10-CM code structure and the post-vaccination follow-up period. We used the self-controlled tree-temporal scan statistic and TreeScan software. Monte Carlo simulation was used to estimate p-values; p = 0.01 was the pre-specified cut-off for statistical significance of a cluster. RESULTS: There were 4.1, 2.6, and 0.4 million Pfizer-BioNTech, Moderna, and Janssen vaccinees, respectively. Clusters after Pfizer-BioNTech vaccination included: (1) unspecified adverse effects, (2) common vaccine reactions, such as fever, myalgia, and headache, (3) myocarditis/pericarditis, and (4) less specific cardiac or respiratory symptoms, all with the strongest clusters generally after Dose 2; and (5) COVID-19/viral pneumonia/sepsis/respiratory failure in the first 3 weeks after Dose 1. Moderna results were similar but without a significant myocarditis/pericarditis cluster. Further investigation suggested the fifth signal group was a manifestation of mRNA vaccine effectiveness after the first 3 weeks. Janssen vaccinees had clusters of unspecified or common vaccine reactions, gait/mobility abnormalities, and muscle weakness. The latter two were deemed to have arisen from confounding related to practices at one site. CONCLUSIONS: We detected post-vaccination clusters of unspecified adverse effects, common vaccine reactions, and, for the mRNA vaccines, chest pain and palpitations, as well as myocarditis/pericarditis after Pfizer-BioNTech Dose 2. Unique advantages of this data mining are its untargeted nature and its inherent adjustment for the multiplicity of diagnoses and risk intervals scanned.

Tree-based data mining for safety assessment of first COVID-19 booster doses in the Vaccine Safety Datalink.

BACKGROUND: The Centers for Disease Control and Prevention's Vaccine Safety Datalink (VSD) has been performing safety surveillance for COVID-19 vaccines since their earliest authorization in the United States. Complementing its real-time surveillance for pre-specified health outcomes using pre-specified risk intervals, the VSD conducts tree-based data-mining to look for clustering of a broad range of health outcomes after COVID-19 vaccination. This study's objective was to use this untargeted, hypothesis-generating approach to assess the safety of first booster doses of Pfizer-BioNTech (BNT162b2), Moderna (mRNA-1273), and Janssen (Ad26.COV2.S) COVID-19 vaccines. METHODS: VSD enrollees receiving a first booster of COVID-19 vaccine through April 2, 2022 were followed for 56 days. Incident diagnoses in inpatient or emergency department settings were analyzed for clustering within both the hierarchical ICD-10-CM code structure and the follow-up period. The self-controlled tree-temporal scan statistic was used, conditioning on the total number of cases for each diagnosis. P-values were estimated by Monte Carlo simulation; p = 0.01 was pre-specified as the cut-off for statistical significance of clusters. RESULTS: More than 2.4 and 1.8 million subjects received Pfizer-BioNTech and Moderna boosters after an mRNA primary series, respectively. Clusters of urticaria/allergy/rash were found during Days 10-15 after the Moderna booster (p = 0.0001). Other outcomes that clustered after mRNA boosters, mostly with p = 0.0001, included unspecified adverse effects, common vaccine-associated reactions like fever and myalgia, and COVID-19. COVID-19 clusters were in Days 1-10 after booster receipt, before boosters would have become effective. There were no noteworthy clusters after boosters following primary Janssen vaccination. CONCLUSIONS: In this untargeted data-mining study of COVID-19 booster vaccination, a cluster of delayed-onset urticaria/allergy/rash was detected after the Moderna booster, as has been reported after Moderna vaccination previously. Other clusters after mRNA boosters were of unspecified or common adverse effects and COVID-19, the latter evidently reflecting immunity to COVID-19 after 10 days.

A COVID-19-ready public health surveillance system: The Food and Drug Administration's Sentinel System.

The US Food and Drug Administration's Sentinel System was established in 2009 to use routinely collected electronic health data for improving the national capability to assess post-market medical product safety. Over more than a decade, Sentinel has become an integral part of FDA's surveillance capabilities and has been used to conduct analyses that have contributed to regulatory decisions. FDA's role in the COVID-19 pandemic response has necessitated an expansion and enhancement of Sentinel. Here we describe how the Sentinel System has supported FDA's response to the COVID-19 pandemic. We highlight new capabilities developed, key data generated to date, and lessons learned, particularly with respect to working with inpatient electronic health record data. Early in the pandemic, Sentinel developed a multi-pronged approach to support FDA's anticipated data and analytic needs. It incorporated new data sources, created a rapidly refreshed database, developed protocols to assess the natural history of COVID-19, validated a diagnosis-code based algorithm for identifying patients with COVID-19 in administrative claims data, and coordinated with other national and international initiatives. Sentinel is poised to answer important questions about the natural history of COVID-19 and is positioned to use this information to study the use, safety, and potentially the effectiveness of medical products used for COVID-19 prevention and treatment.