The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety.
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ABSTRACT:
SUBMITTER: Black SB
PROVIDER: S-EPMC7936550 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe U.S. Food and Drug Administration (FDA) Biologics Effectiveness and Safety (BEST) Initiative conducts active surveillance of adverse events of special interest (AESI) after COVID-19 vaccination. Historical incidence rates (IRs) of AESI are comparators to evaluate safety.MethodsWe estimated IRs of 17 AESI in six administrative claims databases from January 1, 2019, to December 11, 2020: Medicare claims for adults ≥ 65 years and commercial claims (Blue Health Intelligence®, CVS Health, HealthCore Integrated Research Database, IBM® MarketScan® Commercial Database, Optum pre-adjudicated claims) for adults < 65 years. IRs were estimated by sex, age, race/ethnicity (Medicare), and nursing home residency (Medicare) in 2019 and for specific periods in 2020.ResultsThe study included >100 million enrollees annually. In 2019, rates of most AESI increased with age. However, compared with commercially insured adults, Medicare enrollees had lower IRs of anaphylaxis (11 vs 12-19 per 100,000 person-years), appendicitis (80 vs 117-155), and narcolepsy (38 vs 41-53). Rates were higher in males than females for most AESI across databases and varied by race/ethnicity and nursing home status (Medicare). Acute myocardial infarction (Medicare) and anaphylaxis (all databases) IRs varied by season. IRs of most AESI were lower during March-May 2020 compared with March-May 2019 but returned to pre-pandemic levels after May 2020. However, rates of Bell's palsy, Guillain-Barré syndrome, narcolepsy, and hemorrhagic/non-hemorrhagic stroke remained lower in multiple databases after May 2020, whereas some AESI (e.g., disseminated intravascular coagulation) exhibited higher rates after May 2020 compared with 2019.ConclusionAESI background rates varied by database and demographics and fluctuated in March-December 2020, but most returned to pre-pandemic levels after May 2020. It is critical to standardize demographics and consider seasonal and other trends when comparing historical rates with post-vaccination AESI rates in the same database to evaluate COVID-19 vaccine safety.
| S-EPMC9640387 | biostudies-literature
Project description:Using meta-analytic methods, we calculated expected rates of 21 potential adverse events of special interest (AESI) that would occur following COVID-19 vaccination within 1-, 7-, and 42-day intervals without causal associations. Based on these expected rates, if 10,000,000 persons are vaccinated, 0.5, 3.7, and 22.5 Guillain-Barre syndrome cases; 0.3, 2.4, and 14.3 myopericarditis cases; and 236.5, 1655.5, and 9932.8 all-cause deaths would occur coincidentally within 1, 7, and 42 days post-vaccination, respectively. Expected rates of potential AESI can contextualize events associated temporally with immunization, aid in safety signal detection, guide COVID-19 vaccine health communications, and inform COVID-19 vaccine benefit-risk assessments.
| S-EPMC8755334 | biostudies-literature
Project description:BackgroundMaternal immunization has gained traction as a strategy to diminish maternal and young infant mortality attributable to infectious diseases. Background rates of adverse pregnancy outcomes are crucial to interpret results of clinical trials in Sub-Saharan Africa.MethodsWe developed a mathematical model that calculates a clinical trial's expected number of neonatal and maternal deaths at an interim safety assessment based on the person-time observed during different risk windows. This model was compared to crude multiplication of the maternal mortality ratio and neonatal mortality rate by the number of live births. Systematic reviews of severe acute maternal morbidity (SAMM), low birth weight (LBW), prematurity, and major congenital malformations (MCM) in Sub-Saharan African countries were also performed.FindingsAccounting for the person-time observed during different risk periods yields lower, more conservative estimates of expected maternal and neonatal deaths, particularly at an interim safety evaluation soon after a large number of deliveries. Median incidence of SAMM in 16 reports was 40.7 (IQR: 10.6-73.3) per 1,000 total births, and the most common causes were hemorrhage (34%), dystocia (22%), and severe hypertensive disorders of pregnancy (22%). Proportions of liveborn infants who were LBW (median 13.3%, IQR: 9.9-16.4) or premature (median 15.4%, IQR: 10.6-19.1) were similar across geographic region, study design, and institutional setting. The median incidence of MCM per 1,000 live births was 14.4 (IQR: 5.5-17.6), with the musculoskeletal system comprising 30%.InterpretationSome clinical trials assessing whether maternal immunization can improve pregnancy and young infant outcomes in the developing world have made ethics-based decisions not to use a pure placebo control. Consequently, reliable background rates of adverse pregnancy outcomes are necessary to distinguish between vaccine benefits and safety concerns. Local studies that quantify population-based background rates of adverse pregnancy outcomes will improve safety assessment of interventions during pregnancy.
| S-EPMC3464282 | biostudies-literature
Project description:BackgroundDetermining background rates of medical conditions identified as adverse events of special interest (AESI) that may occur following COVID-19 vaccination is important for contextualising and investigating potential vaccine safety signals.MethodsWe conducted a retrospective population-based cohort study using linked emergency department, hospitalisation and death data for 2017 and 2018 from Australia's most populous state, New South Wales. Incident cases of select neurological conditions, arterial or venous thromboembolic conditions, secondary thrombocytopenia, myocarditis/pericarditis, and unique events of anaphylaxis and generalised convulsions were identified using internationally agreed upon diagnostic (ICD-10) codes. State-specific rates per 100,000 person-years were calculated, with further stratification by age group and sex where clinically relevant to the condition, and the number of expected cases nationally in one and 6 weeks was estimated.ResultsBackground rates of selected neurological conditions were low with the exception of generalised convulsions for which 1,599-1,872 cases were estimated nationally in a 1-week period in the absence of vaccination. Using a narrow case definition, rates of Guillain-Barré Syndrome (3.9 per 100,000 person-years) were higher than international rates reported elsewhere. Thromboembolic and cerebral venous sinus thrombosis event rates increased with age. Myocarditis occurred more commonly in males, and was highest in males aged 18-24 years, with an estimated 1-4 cases expected nationally in a 1-week period.ConclusionsUsing routinely collected linked healthcare data provides localised estimates of background rates of new onset or periodic AESI which enables rapid estimation of observed-versus-expected rates of events reported following COVID-19 vaccination. This Australian-specific analysis contributes AESI background rates which can be compared with those from other countries to enhance understanding of geographic variability in the frequency of specific AESI in the absence of vaccination, and can be utilised for signal detection during program implementation.
| S-EPMC10110935 | biostudies-literature
Project description: Not available
| S-EPMC4425825 | biostudies-literature
Project description:IntroductionAdverse events following immunization (AEFIs) are unwanted or unexpected health outcomes following vaccination, which may or may not be causally-linked to vaccines. AEFI reporting is important to post-marketing vaccine safety surveillance and has the potential to identify new or rare AEFIs, show increases in known AEFIs, and help to maintain public confidence in vaccine programs. Knowledge of the expected incidence (i.e. background rate) of a possible AEFI is essential to the investigation of vaccine safety signals. We selected three rarely reported AEFIs representing the spectrum of causal association with vaccines, from proven (immune thrombocytopenia [ITP]) to questioned (Kawasaki disease [KD]) to unsubstantiated (multiple sclerosis [MS]) and determined their background rates.MethodsWe extracted data on hospitalizations (CIHI Discharge Abstract Database) for ITP, KD, and MS among Ontario children for the period 2005 to 2014 from IntelliHEALTH. As ITP can be managed without hospitalization, we also extracted emergency department (ED) visits from the CIHI National Ambulatory Care Reporting System. For all conditions, we only counted the first visit and if the same child had both an ED visit and a hospitalization for ITP, only the hospitalization was included. We calculated rates by year, age group and sex using population estimates from 2005-2014, focusing on age groups within the Ontario immunization schedule around vaccine(s) of interest.ResultsPer 100,000 population, annual age-specific incidence of ITP in children age 1 to 7 years ranged from 8.9 to 12.2 and annual incidence of KD in children less than 5 years ranged from 19.1 to 32.1. Average annualized incidence of adolescent (11-17 years) MS across the study period was 0.8 per 100,000.DiscussionDespite limitations, including lack of clinical validation, this study provides an example of how health administrative data can be used to determine background rates which may assist with interpretation of passive vaccine safety surveillance.
| S-EPMC6333343 | biostudies-literature
Project description:Nicotinamide (NAM) at doses far above those recommended for vitamins is suggested to be effective against a wide spectrum of diseases and conditions, including neurological dysfunctions, depression and other psychological disorders, and inflammatory diseases. Recent increases in public awareness on possible pro-longevity effects of nicotinamide adenine dinucleotide (NAD+) precursors have caused further growth of NAM consumption not only for clinical treatments, but also as a dietary supplement, raising concerns on the safety of its long-term use. However, possible adverse effects and their mechanisms are poorly understood. High-level NAM administration can exert negative effects through multiple routes. For example, NAM by itself inhibits poly(ADP-ribose) polymerases (PARPs), which protect genome integrity. Elevation of the NAD+ pool alters cellular energy metabolism. Meanwhile, high-level NAM alters cellular methyl metabolism and affects methylation of DNA and proteins, leading to changes in cellular transcriptome and proteome. Also, methyl metabolites of NAM, namely methylnicotinamide, are predicted to play roles in certain diseases and conditions. In this review, a collective literature search was performed to provide a comprehensive list of possible adverse effects of NAM and to provide understanding of their underlying mechanisms and assessment of the raised safety concerns. Our review assures safety in current usage level of NAM, but also finds potential risks for epigenetic alterations associated with chronic use of NAM at high doses. It also suggests directions of the future studies to ensure safer application of NAM.
| S-EPMC7277745 | biostudies-literature
Project description:Post licensure surveillance of adverse events following immunization (AEFI) is a fundamental activity to improve safety and maintain public confidence in vaccines. Since 2011, the Liguria Region has been involved in the inter-regional project of post-marketing surveillance of AEFI, coordinated by the Italian Medicine Agency and the Veneto region. The main objectives of the project are: (1) to coordinate the surveillance activities in the 8 Italian Regions included in the project; (2) to encourage the signal of AEFI by healthcare workers and patients; (3) to organize education activities addressed to health care workers, and, finally; (4) to establish vaccination counseling services in each Region. In particular, the Ligurian multidisciplinary team, composed by physicians expert in the field of vaccination and pharmacists, is involved in the causality assessment between vaccines and all adverse events signaled within the Liguria Region and in the analysis of all adverse events signaled in Italy as possibly related to influenza vaccines. During 2013, the team has organized 4 courses, addressed to healthcare personnel of vaccination outpatient clinics, focused on European and Italian legislation on pharmaco-vigilance and vaccine-vigilance and aimed at promoting signal of AEFI. Since October 2013, the Liguria Region has been participating to the inter-regional project of active surveillance of adverse events aimed at promoting the signal of AEFI by parents of vaccinated infants. After two years of implementation of the project both the number of reported AEFI and the reporting rate per 100 000 administered doses of vaccine increased. The activities need to be consolidated in the next years in order to guarantee high standard of vaccine safety, maintain the confidence in current immunization programs and reach optimal vaccination coverage rate.
| S-EPMC4514437 | biostudies-other
Project description:The Vaccine Adverse Event Reporting System (VAERS) is a passive reporting system, used for monitoring the safety of all US licensed vaccines. In March 2008, ACAM2000(®) replaced Dryvax(®) as the only licensed smallpox vaccine and is administered to all persons entering military service and certain civilian researchers. In 2011, routine data mining of VAERS identified a vaccine safety concern resulting in acute ischemic cardiac events (ICE) following ACAM2000(®).During March 1, 2008 through June 30, 2013, we reviewed all serious reports received following ACAM2000(®)and classified them by diagnostic category. We identified possible ICE cases by searching the Medical Dictionary for Regulatory Affairs (MedDRA(®)) terms for "myocardial ischaemia," "acute myocardial infarction," "myocardial infarction," and "ischaemia," and applied standardized surveillance case definitions.VAERS received 1149 reports following ACAM2000(®) administration; 169 (14.7%) were serious (resulting in permanent disability, hospitalization or prolongation of hospitalization, life-threatening illness or death), including one death. The two most frequent diagnostic categories for serious reports were cardiovascular and other infectious conditions. The MedDRA(®) search found 31 reports of possible ICE after receipt of ACAM2000(®) vaccine. Of a total 30 possible ICE cases with demographic information, all but one was male; the age range was 20-45 years (median 32) and median interval to onset of symptoms was 12 days. On clinical review there were 16 cases of myocarditis/pericarditis and 15 ICE cases.Our review of the data mining signal did not substantiate the concerns about ICE after ACAM2000(®). Our study also suggests that with current pre-vaccination screening, cardiac morbidity in generally healthy vaccinated populations remains uncommon.
| S-EPMC5946322 | biostudies-other
Project description:ObjectiveAutomated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression of rare but severe vaccine adverse events (AEs). This study implemented and evaluated state-of-the-art deep learning algorithms for named entity recognition to extract nervous system disorder-related events from vaccine safety reports.Materials and methodsWe collected Guillain-Barré syndrome (GBS) related influenza vaccine safety reports from the Vaccine Adverse Event Reporting System (VAERS) from 1990 to 2016. VAERS reports were selected and manually annotated with major entities related to nervous system disorders, including, investigation, nervous_AE, other_AE, procedure, social_circumstance, and temporal_expression. A variety of conventional machine learning and deep learning algorithms were then evaluated for the extraction of the above entities. We further pretrained domain-specific BERT (Bidirectional Encoder Representations from Transformers) using VAERS reports (VAERS BERT) and compared its performance with existing models.Results and conclusionsNinety-one VAERS reports were annotated, resulting in 2512 entities. The corpus was made publicly available to promote community efforts on vaccine AEs identification. Deep learning-based methods (eg, bi-long short-term memory and BERT models) outperformed conventional machine learning-based methods (ie, conditional random fields with extensive features). The BioBERT large model achieved the highest exact match F-1 scores on nervous_AE, procedure, social_circumstance, and temporal_expression; while VAERS BERT large models achieved the highest exact match F-1 scores on investigation and other_AE. An ensemble of these 2 models achieved the highest exact match microaveraged F-1 score at 0.6802 and the second highest lenient match microaveraged F-1 score at 0.8078 among peer models.
| S-EPMC8279785 | biostudies-literature