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Wu JJ, Hauben M, Younus M. Current Approaches in Postapproval Vaccine Safety Studies Using Real-World Data: A Systematic Review of Published Literature. Clin Ther 2024:S0149-2918(24)00142-5. [PMID: 39142925 DOI: 10.1016/j.clinthera.2024.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 05/06/2024] [Accepted: 06/05/2024] [Indexed: 08/16/2024]
Abstract
PURPOSE Well-designed observational postmarketing studies using real-world data (RWD) are critical in supporting an evidence base and bolstering public confidence in vaccine safety. This systematic review presents current research methodologies in vaccine safety research in postapproval settings, technological advancements contributing to research resources and capabilities, and their major strengths and limitations. METHODS A comprehensive search was conducted using PubMed to identify relevant articles published from January 1, 2019, to December 31, 2022. Eligible studies were summarized overall by study design and other study characteristics (eg, country, vaccine studied, types of data source, and study population). An in-depth review of select studies representative of conventional or new designs, analytical approaches, or data collection methods was conducted to summarize current methods in vaccine safety research. FINDINGS Out of 977 articles screened for inclusion, 135 were reviewed. The review shows that recent advancements in scientific methods, digital technology, and analytic approaches have significantly contributed to postapproval vaccine safety studies using RWD. "Near real-time surveillance" using large datasets (via collaborative or distributed databases) has been used to facilitate rapid signal detection that complements passive surveillance. There was increasing appreciation for self-controlled case-only designs (self-controlled case series and self-controlled risk interval) to assess acute-onset safety outcomes, artificial intelligence, and natural language processing to improve outcome accuracy and study timeliness and emerging artificial intelligence-based analysis to capture adverse events from social media platforms. IMPLICATIONS Continued development in the area of vaccine safety research methodologies using RWD is warranted. The future of successful vaccine safety research, especially evaluation of rare safety events, is likely to comprise digital technologies including linking RWD networks, machine learning, and advanced analytic methods to generate rapid and robust real-world safety information.
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Affiliation(s)
- Juan Joanne Wu
- Safety Surveillance Research, Worldwide Medical and Safety, Pfizer Inc, New York, NY
| | - Manfred Hauben
- Department of Family and Community Medicine, New York Medical College, Valhalla, NY and Truliant Consulting, Baltimore, Maryland
| | - Muhammad Younus
- Safety Surveillance Research, Worldwide Medical and Safety, Pfizer Inc, New York, NY.
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Banga S, Khromava A, Serradell L, Chabanon AL, Pan C, Estevez I, Schilsky S, Kreisberg H. Background incidence rates of health outcomes of interest for COVID-19 vaccine safety monitoring in a US population: a claims database analysis. BMJ Open 2024; 14:e083947. [PMID: 38991681 PMCID: PMC11243135 DOI: 10.1136/bmjopen-2024-083947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 06/04/2024] [Indexed: 07/13/2024] Open
Abstract
OBJECTIVE To evaluate background incidence rates of 59 health outcomes of interest (HOI) in a diverse population, including important subpopulations, during the pre-COVID-19 era (1 January 2017-31 December 2019) and the COVID-19 era (1 March 2020-31 December 2020), before the introduction of COVID-19 vaccines. DESIGN Observational retrospective cohort study. Annual incidence rates and 95% confidence intervals (CIs) of HOIs were estimated for each population of interest, stratified by: age, sex, age and sex and seasonality. DATA SOURCE Optum's de-identified Clinformatics Data Mart Database (CDM). PARTICIPANTS Individuals from the US general population and four subgroups of interest: influenza-vaccinated, paediatric (<18 years of age), elderly (≥65 years of age) and pregnant women. RESULTS During the COVID-19 era, the incidence of several cardiac conditions, coagulation disorders and acute liver injury increased across all populations assessed while the rates of some dermatological and neurological HOIs decreased relative to the pre-COVID-19 era. The incidence of acute respiratory distress syndrome (ARDS) varied considerably by subgroup: among the elderly, it decreased annually during the pre-COVID-19 era but peaked during the COVID-19 era; among pregnant women, it slightly increased annually during the pre-COVID-19 era and substantially increased during the COVID-19 era; among paediatrics, it decreased annually over the entire study. The incidence of the majority of HOIs increased with age, but were generally comparable between sexes with few exceptions. Cardiac, gastrointestinal, neurological and haematological HOIs, along with acute kidney injury and ARDS, were more common in males, whereas several immunological HOIs and chilblain-like lesions were more common in females. Pregnancy-related HOIs did not increase during the COVID-19 era, except for spontaneous abortions which increased annually over the entire study. CONCLUSION These observations help contextualise fluctuations in background rates of adverse events noted during the COVID-19 era, and provide insight on how their use may impact safety surveillance for other vaccines.
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Lu Y, Matuska K, Nadimpalli G, Ma Y, Duma N, Zhang HT, Chiang Y, Lyu H, Chillarige Y, Kelman JA, Forshee RA, Anderson SA. Stroke Risk After COVID-19 Bivalent Vaccination Among US Older Adults. JAMA 2024; 331:938-950. [PMID: 38502075 PMCID: PMC10951737 DOI: 10.1001/jama.2024.1059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 01/24/2024] [Indexed: 03/20/2024]
Abstract
Importance In January 2023, the US Centers for Disease Control and Prevention and the US Food and Drug Administration noted a safety concern for ischemic stroke among adults aged 65 years or older who received the Pfizer-BioNTech BNT162b2; WT/OMI BA.4/BA.5 COVID-19 bivalent vaccine. Objective To evaluate stroke risk after administration of (1) either brand of the COVID-19 bivalent vaccine, (2) either brand of the COVID-19 bivalent plus a high-dose or adjuvanted influenza vaccine on the same day (concomitant administration), and (3) a high-dose or adjuvanted influenza vaccine. Design, Setting, and Participants Self-controlled case series including 11 001 Medicare beneficiaries aged 65 years or older who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine (among 5 397 278 vaccinated individuals). The study period was August 31, 2022, through February 4, 2023. Exposures Receipt of (1) either brand of the COVID-19 bivalent vaccine (primary) or (2) a high-dose or adjuvanted influenza vaccine (secondary). Main Outcomes and Measures Stroke risk (nonhemorrhagic stroke, transient ischemic attack, combined outcome of nonhemorrhagic stroke or transient ischemic attack, or hemorrhagic stroke) during the 1- to 21-day or 22- to 42-day risk window after vaccination vs the 43- to 90-day control window. Results There were 5 397 278 Medicare beneficiaries who received either brand of the COVID-19 bivalent vaccine (median age, 74 years [IQR, 70-80 years]; 56% were women). Among the 11 001 beneficiaries who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine, there were no statistically significant associations between either brand of the COVID-19 bivalent vaccine and the outcomes of nonhemorrhagic stroke, transient ischemic attack, nonhemorrhagic stroke or transient ischemic attack, or hemorrhagic stroke during the 1- to 21-day or 22- to 42-day risk window vs the 43- to 90-day control window (incidence rate ratio [IRR] range, 0.72-1.12). Among the 4596 beneficiaries who experienced stroke after concomitant administration of either brand of the COVID-19 bivalent vaccine plus a high-dose or adjuvanted influenza vaccine, there was a statistically significant association between vaccination and nonhemorrhagic stroke during the 22- to 42-day risk window for the Pfizer-BioNTech BNT162b2; WT/OMI BA.4/BA.5 COVID-19 bivalent vaccine (IRR, 1.20 [95% CI, 1.01-1.42]; risk difference/100 000 doses, 3.13 [95% CI, 0.05-6.22]) and a statistically significant association between vaccination and transient ischemic attack during the 1- to 21-day risk window for the Moderna mRNA-1273.222 COVID-19 bivalent vaccine (IRR, 1.35 [95% CI, 1.06-1.74]; risk difference/100 000 doses, 3.33 [95% CI, 0.46-6.20]). Among the 21 345 beneficiaries who experienced stroke after administration of a high-dose or adjuvanted influenza vaccine, there was a statistically significant association between vaccination and nonhemorrhagic stroke during the 22- to 42-day risk window (IRR, 1.09 [95% CI, 1.02-1.17]; risk difference/100 000 doses, 1.65 [95% CI, 0.43-2.87]). Conclusions and Relevance Among Medicare beneficiaries aged 65 years or older who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine, there was no evidence of a significantly elevated risk for stroke during the days immediately after vaccination.
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MESH Headings
- Aged
- Female
- Humans
- Male
- 2019-nCoV Vaccine mRNA-1273/adverse effects
- 2019-nCoV Vaccine mRNA-1273/therapeutic use
- Adjuvants, Immunologic/adverse effects
- Adjuvants, Immunologic/therapeutic use
- BNT162 Vaccine/adverse effects
- BNT162 Vaccine/therapeutic use
- COVID-19/prevention & control
- COVID-19 Vaccines/adverse effects
- COVID-19 Vaccines/therapeutic use
- Hemorrhagic Stroke/chemically induced
- Hemorrhagic Stroke/epidemiology
- Hemorrhagic Stroke/etiology
- Influenza Vaccines/adverse effects
- Influenza Vaccines/therapeutic use
- Ischemic Attack, Transient/chemically induced
- Ischemic Attack, Transient/epidemiology
- Ischemic Attack, Transient/etiology
- Medicare
- Stroke/epidemiology
- Stroke/etiology
- Stroke/prevention & control
- United States/epidemiology
- Vaccination/adverse effects
- Vaccination/methods
- Vaccines, Combined/adverse effects
- Vaccines, Combined/therapeutic use
- Centers for Disease Control and Prevention, U.S./statistics & numerical data
- United States Food and Drug Administration/statistics & numerical data
- Ischemic Stroke/chemically induced
- Ischemic Stroke/epidemiology
- Ischemic Stroke/etiology
- Influenza, Human/prevention & control
- Aged, 80 and over
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Affiliation(s)
- Yun Lu
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | | | | | - Yuxin Ma
- Acumen LLC, Burlingame, California
| | | | - Henry T Zhang
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | | | - Hai Lyu
- Acumen LLC, Burlingame, California
| | | | | | - Richard A Forshee
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | - Steven A Anderson
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
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Dreyfus J, Munnangi S, Bengtsson C, Correia B, Figueiredo R, Stark JH, Zawora M, Riddle MS, Maguire JD, Jiang Q, Ianos C, Naredo Turrado J, Svanström H, Bailey S, DeKoven M. Background incidence rates of health outcomes in populations at risk for Lyme disease using US administrative claims data. Vaccine 2024; 42:1094-1107. [PMID: 38262807 DOI: 10.1016/j.vaccine.2024.01.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/09/2024] [Accepted: 01/12/2024] [Indexed: 01/25/2024]
Abstract
BACKGROUND Background incidence rates (IRs) of health outcomes in Lyme disease endemic regions are useful to contextualize events reported during Lyme disease vaccine clinical trials or post-marketing. The objective of this study was to estimate and compare IRs of health outcomes in Lyme disease endemic versus non-endemic regions in the US during pre-COVID and COVID era timeframes. METHODS IQVIA PharMetrics® Plus commercial claims database was used to estimate IRs of 64 outcomes relevant to vaccine safety monitoring in the US during January 1, 2017-December 31, 2019 and January 1, 2020-December 31, 2021. Analyses included all individuals aged ≥ 2 years with ≥ 1 year of continuous enrollment. Outcomes were defined by International Classification of Diseases Clinical Modification, 10th Revision (ICD-10-CM) diagnosis codes. IRs and 95 % confidence intervals (CIs) were calculated for each outcome and compared between endemic vs. non-endemic regions, and pre-COVID vs. COVID era using IR ratios (IRR). RESULTS The study population included 8.7 million (M) in endemic and 27.8 M in non-endemic regions. Mean age and sex were similar in endemic and non-endemic regions. In both study periods, the IRs were statistically higher in endemic regions for anaphylaxis, meningoencephalitis, myocarditis/pericarditis, and rash (including erythema migrans) as compared with non-endemic regions. Conversely, significantly lower IRs were observed in endemic regions for acute kidney injury, disseminated intravascular coagulation, heart failure, myelitis, myopathies, and systemic lupus erythematosus in both study periods. Most outcomes were statistically less frequent during the COVID-era. CONCLUSION This study identified potential differences between Lyme endemic and non-endemic regions of the US in background IRs of health conditions during pre-COVID and COVID era timeframes to inform Lyme disease vaccine safety monitoring. These regional and temporal differences in background IRs should be considered when contextualizing possible safety signals in clinical trials and post-marketing of a vaccine targeted at Lyme disease prevention.
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Affiliation(s)
| | | | | | | | | | - James H Stark
- Vaccines, Antivirals, and Evidence Generation, Medical Affairs, Pfizer Biopharma Group, Cambridge, MA, USA
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Hayes KN, Harris DA, Zullo AR, Djibo DA, Smith-Ray RL, Taitel MS, Singh TG, McMahill-Walraven C, Chachlani P, Wen KJ, McCarthy EP, Gravenstein S, McCurdy S, Baird KE, Moran D, Fenson D, Deng Y, Mor V. Data resource profile: COVid VAXines effects on the aged (COVVAXAGE). Int J Popul Data Sci 2023; 8:2170. [PMID: 38425722 PMCID: PMC10900297 DOI: 10.23889/ijpds.v8i6.2170] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024] Open
Abstract
Background To improve the assessment of COVID-19 vaccine use, safety, and effectiveness in older adults and persons with complex multimorbidity, the COVid VAXines Effects on the Aged (COVVAXAGE) database was established by linking CVS Health and Walgreens pharmacy customers to Medicare claims. Methods We deterministically linked CVS Health and Walgreens customers who had a pharmacy dispensation/encounter paid for by Medicare to Medicare enrollment and claims records. Linked data include U.S. Medicare claims, Medicare enrollment files, and community pharmacy records. The data currently span 01/01/2016 to 08/31/2022. "Research-ready" files were created, with weekly indicators for vaccinations, censoring, death, enrollment, demographics, and comorbidities. Data are updated quarterly. Results As of November 2022, records for 27,086,723 CVS Health and 23,510,025 Walgreens unique customer IDs were identified for potential linkage. Approximately 91% of customers were matched to a Medicare beneficiary ID (95% for those aged 65 years or older). In the final linked cohort, there were 38,250,873 unique beneficiaries representing ~60% of the Medicare population. Among those alive and enrolled in Medicare as of January 1, 2020 (n = 33,721,568; average age = 73 years, 74% White, 51% Medicare Fee-for-Service, and 11% dual-eligible for Medicaid), the average follow-up time was 130 weeks. The cohort contains 16,021,055 beneficiaries with evidence a first COVID-19 vaccine dose. Data are stored on the secure Medicare & Medicaid Resource Information Center Health & Aging Data Enclave. Data access Investigators with funded or in-progress funding applications to the National Institute on Aging who are interested in learning more about the database should contact Dr Vincent Mor [Vincent_mor@brown.edu] and Dr Kaleen Hayes [kaley_hayes@brown.edu]. A data dictionary can be provided under reasonable request. Conclusions The COVVAXAGE cohort is a large and diverse cohort that can be used for the ongoing evaluation of COVID-19 vaccine use and other research questions relevant to the Medicare population.
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Affiliation(s)
- Kaleen N. Hayes
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
| | - Daniel A. Harris
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
| | - Andrew R. Zullo
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA, 02903
- Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, USA, 02903
| | - Djeneba Audrey Djibo
- CVS Health Clinical Trial Services, Safety, Surveillance & Collaboration, Blue Bell, PA, USA, 19422
| | - Renae L. Smith-Ray
- Walgreens Center for Health & Wellbeing Research, Walgreen Company, Deerfield, IL, USA, 60015
| | - Michael S. Taitel
- Walgreens Center for Health & Wellbeing Research, Walgreen Company, Deerfield, IL, USA, 60015
| | - Tanya G. Singh
- Walgreens Center for Health & Wellbeing Research, Walgreen Company, Deerfield, IL, USA, 60015
| | - Cheryl McMahill-Walraven
- CVS Health Clinical Trial Services, Safety, Surveillance & Collaboration, Blue Bell, PA, USA, 19422
| | - Preeti Chachlani
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
| | - Katherine J. Wen
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
- Department of Medicine, Health, and Society, Vanderbilt University, Nashville, TN, USA, 37240
| | - Ellen P. McCarthy
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA, 02131
- Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA, 02215
| | - Stefan Gravenstein
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
- Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, USA, 02903
- Division of Geriatrics, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA, 02903
| | | | | | | | | | - Yalin Deng
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
| | - Vincent Mor
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI, USA, 02903
- Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, USA, 02903
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Phillips A, Jiang Y, Walsh D, Andrews N, Artama M, Clothier H, Cullen L, Deng L, Escolano S, Gentile A, Gidding G, Giglio N, Junker T, Huang W, Janjua N, Kwong J, Li J, Nasreen S, Naus M, Naveed Z, Pillsbury A, Stowe J, Vo T, Buttery J, Petousis-Harris H, Black S, Hviid A. Background rates of adverse events of special interest for COVID-19 vaccines: A multinational Global Vaccine Data Network (GVDN) analysis. Vaccine 2023; 41:6227-6238. [PMID: 37673715 DOI: 10.1016/j.vaccine.2023.08.079] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND The Global COVID Vaccine Safety (GCoVS) project was established in 2021 under the multinational Global Vaccine Data Network (GVDN) consortium to facilitate the rapid assessment of the safety of newly introduced vaccines. This study analyzed data from GVDN member sites on the background incidence rates of conditions designated as adverse events of special interest (AESI) for COVID-19 vaccine safety monitoring. METHODS Eleven GVDN global sites obtained data from national or regional healthcare databases using standardized methods. Incident events of 13 pre-defined AESI were included for a pre-pandemic period (2015-19) and the first pandemic year (2020). Background incidence rates (IR) and 95% confidence intervals (CI) were calculated for inpatient and emergency department encounters, stratified by age and sex, and compared between pre-pandemic and pandemic periods using incidence rate ratios. RESULTS An estimated 197 million people contributed 1,189,652,926 person-years of follow-up time. Among inpatients in the pre-pandemic period (2015-19), generalized seizures were the most common neurological AESI (IR ranged from 22.15 [95% CI 19.01-25.65] to 278.82 [278.20-279.44] per 100,000 person-years); acute disseminated encephalomyelitis was the least common (<0.5 per 100,000 person-years at most sites). Pulmonary embolism was the most common thrombotic event (IR 45.34 [95% CI 44.85-45.84] to 93.77 [95% CI 93.46-94.08] per 100,000 person-years). The IR of myocarditis ranged from 1.60 [(95% CI 1.45-1.76) to 7.76 (95% CI 7.46-8.08) per 100,000 person-years. The IR of several AESI varied by site, healthcare setting, age and sex. The IR of some AESI were notably different in 2020 compared to 2015-19. CONCLUSION Background incidence of AESIs exhibited some variability across study sites and between pre-pandemic and pandemic periods. These findings will contribute to global vaccine safety surveillance and research.
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Affiliation(s)
- A Phillips
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia
| | - Y Jiang
- Department of Statistics, University of Auckland, New Zealand; Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand
| | - D Walsh
- Department of Statistics, University of Auckland, New Zealand; Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand
| | - N Andrews
- UK Health Security Agency, London, UK
| | - M Artama
- Faculty of Social Sciences, Tampere University, Finland
| | - H Clothier
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - L Cullen
- Public Health Scotland, Edinburgh, Scotland, UK
| | - L Deng
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia
| | - S Escolano
- Université Paris-Saclay, UVSQ, Inserm, CESP, High Dimensional Biostatistics for Drug Safety and Genomics, Villejuif, France
| | - A Gentile
- Hospital de Niños Ricardo Gutierrez Epidemiology Department Buenos Aires City, Argentina
| | - G Gidding
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia; The University of Sydney Northern Clinical School, Australia
| | - N Giglio
- Hospital de Niños Ricardo Gutierrez Epidemiology Department Buenos Aires City, Argentina
| | - T Junker
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - W Huang
- Global Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan; National Taiwan University Children's Hospital, Taipei, Taiwan
| | - N Janjua
- British Columbia Centre for Disease Control, Vancouver, Canada; School of Population and Public Health, University of British Columbia, Vancouver, Canada; Centre for Health Evaluation and Outcome Sciences, St Paul's Hospital, Vancouver, Canada
| | - J Kwong
- ICES, Toronto, Ontario, Canada; Public Health Ontario, Toronto, Ontario, Canada; Department of Family and Community Medicine, Temerty Faculty of Medicine and the Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - J Li
- British Columbia Centre for Disease Control, Vancouver, Canada
| | - S Nasreen
- ICES, Toronto, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - M Naus
- British Columbia Centre for Disease Control, Vancouver, Canada; School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - Z Naveed
- School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - A Pillsbury
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia
| | - J Stowe
- UK Health Security Agency, London, UK
| | - T Vo
- Faculty of Social Sciences, Tampere University, Finland; Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - J Buttery
- Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand; Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - H Petousis-Harris
- Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand; Associate Professor, School of Population Health, University of Auckland, New Zealand
| | - S Black
- Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand
| | - A Hviid
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark; Pharmacovigilance Research Center, Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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7
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Harris DA, Hayes KN, Zullo AR, Mor V, Chachlani P, Deng Y, McCarthy EP, Djibo DA, McMahill-Walraven CN, Gravenstein S. Comparative Risks of Potential Adverse Events Following COVID-19 mRNA Vaccination Among Older US Adults. JAMA Netw Open 2023; 6:e2326852. [PMID: 37531110 PMCID: PMC10398407 DOI: 10.1001/jamanetworkopen.2023.26852] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 06/21/2023] [Indexed: 08/03/2023] Open
Abstract
Importance Head-to-head safety comparisons of the mRNA vaccines for SARS-CoV-2 are needed for decision making; however, current evidence generalizes poorly to older adults, lacks sufficient adjustment, and inadequately captures events shortly after vaccination. Additionally, no studies to date have explored potential variation in comparative vaccine safety across subgroups with frailty or an increased risk of adverse events, information that would be useful for tailoring clinical decisions. Objective To compare the risk of adverse events between mRNA vaccines for COVID-19 (mRNA-1273 and BNT162b2) overall, by frailty level, and by prior history of the adverse events of interest. Design, Setting, and Participants This retrospective cohort study was conducted between December 11, 2020, and July 11, 2021, with 28 days of follow-up following the week of vaccination. A novel linked database of community pharmacy and Medicare claims data was used, representing more than 50% of the US Medicare population. Community-dwelling, fee-for-service beneficiaries aged 66 years or older who received mRNA-1273 vs BNT162b2 as their first COVID-19 vaccine were identified. Data analysis began on October 18, 2022. Exposure Dose 1 of mRNA-1273 vs BNT162b2 vaccine. Main Outcomes and Measures Twelve potential adverse events (eg, pulmonary embolism, thrombocytopenia purpura, and myocarditis) were assessed individually. Frailty was measured using a claims-based frailty index, with beneficiaries being categorized as nonfrail, prefrail, and frail. The risk of diagnosed COVID-19 was assessed as a secondary outcome. Generalized linear models estimated covariate-adjusted risk ratios (RRs) and risk differences (RDs) with 95% CIs. Results This study included 6 388 196 eligible individuals who received the mRNA-1273 or BNT162b2 vaccine. Their mean (SD) age was 76.3 (7.5) years, 59.4% were women, and 86.5% were White. A total of 38.1% of individuals were categorized as prefrail and 6.0% as frail. The risk of all outcomes was low in both vaccine groups. In adjusted models, the mRNA-1273 vaccine was associated with a lower risk of pulmonary embolism (RR, 0.96 [95% CI, 0.93-1.00]; RD, 9 [95% CI, 1-16] events per 100 000 persons) and other adverse events in subgroup analyses (eg, 11.0% lower risk of thrombocytopenia purpura among individuals categorized as nonfrail). The mRNA-1273 vaccine was also associated with a lower risk of diagnosed COVID-19 (RR, 0.86 [95% CI, 0.83-0.87]), a benefit that was attenuated by frailty level (frail: RR, 0.94 [95% CI, 0.89-0.99]). Conclusions and Relevance In this cohort study of older US adults, the mRNA-1273 vaccine was associated with a slightly lower risk of several adverse events compared with BNT162b2, possibly due to greater protection against COVID-19. Future research should seek to formally disentangle differences in vaccine safety and effectiveness and consider the role of frailty in assessments of COVID-19 vaccine performance.
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Affiliation(s)
- Daniel A. Harris
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Kaleen N. Hayes
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Andrew R. Zullo
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
| | - Vincent Mor
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Providence Medical Center Veterans Administration Research Service, Providence, Rhode Island
| | - Preeti Chachlani
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Yalin Deng
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Ellen P. McCarthy
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts
- Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | | | | | - Stefan Gravenstein
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Division of Geriatrics and Palliative Medicine, Alpert Medical School of Brown University, Providence, Rhode Island
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8
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Yang Y, Huang L. Neurological Disorders following COVID-19 Vaccination. Vaccines (Basel) 2023; 11:1114. [PMID: 37376503 DOI: 10.3390/vaccines11061114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 06/08/2023] [Accepted: 06/14/2023] [Indexed: 06/29/2023] Open
Abstract
Nowadays, people all over the world have been receiving different types of coronavirus disease 2019 (COVID-19) vaccines. While their effectiveness has been well recognized, various post-vaccination disorders are not fully understood. In this review, we discuss neurological disorders related to vascular, immune, infectious, and functional factors following COVID-19 vaccination, and attempt to provide neuroscientists, psychiatrists, and vaccination staff with a reference for the diagnosis and treatment of these diseases. These disorders may present as a recurrence of previous neurological disorders or new-onset diseases. Their incidence rate, host and vaccine characteristics, clinical manifestations, treatment, and prognosis differ significantly. The pathogenesis of many of them remains unclear, and further studies are needed to provide more evidence. The incidence rate of severe neurological disorders is relatively low, most of which are reversible or treatable. Therefore, the benefits of vaccination outweigh the risk of COVID-19 infection, especially among fragile populations.
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Affiliation(s)
- Ying Yang
- Department of Infectious Diseases, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
| | - Lisu Huang
- Department of Infectious Diseases, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China
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9
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Pillsbury A, Phillips A, Deng L, Quinn H, Macartney K, Gidding H. Background incidence rates of selected adverse events of special interest (AESI) to monitor the safety of COVID-19 vaccines. Vaccine 2023; 41:3422-3428. [PMID: 37088604 PMCID: PMC10110935 DOI: 10.1016/j.vaccine.2023.04.041] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND Determining 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. METHODS We 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. RESULTS Background 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. CONCLUSIONS Using 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.
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Affiliation(s)
- Alexis Pillsbury
- National Centre for Immunisation Research and Surveillance, Children's Hospital at Westmead, Westmead, NSW, Australia; The University of Sydney Children's Hospital Westmead Clinical School, Westmead, NSW, Australia.
| | - Anastasia Phillips
- National Centre for Immunisation Research and Surveillance, Children's Hospital at Westmead, Westmead, NSW, Australia.
| | - Lucy Deng
- National Centre for Immunisation Research and Surveillance, Children's Hospital at Westmead, Westmead, NSW, Australia; The University of Sydney Children's Hospital Westmead Clinical School, Westmead, NSW, Australia.
| | - Helen Quinn
- National Centre for Immunisation Research and Surveillance, Children's Hospital at Westmead, Westmead, NSW, Australia; The University of Sydney Children's Hospital Westmead Clinical School, Westmead, NSW, Australia.
| | - Kristine Macartney
- National Centre for Immunisation Research and Surveillance, Children's Hospital at Westmead, Westmead, NSW, Australia; The University of Sydney Children's Hospital Westmead Clinical School, Westmead, NSW, Australia.
| | - Heather Gidding
- National Centre for Immunisation Research and Surveillance, Children's Hospital at Westmead, Westmead, NSW, Australia; The University of Sydney Northern Clinical School, St Leonards, NSW, Australia; Women and Babies Research, Kolling Institute, Northern Sydney Local Health District, St Leonards, NSW, Australia; School of Population Health, UNSW Medicine, University of NSW, Sydney, NSW, Australia.
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10
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Wong HL, Tworkoski E, Ke Zhou C, Hu M, Thompson D, Lufkin B, Do R, Feinberg L, Chillarige Y, Dimova R, Lloyd PC, MaCurdy T, Forshee RA, Kelman JA, Shoaibi A, Anderson SA. Surveillance of COVID-19 vaccine safety among elderly persons aged 65 years and older. Vaccine 2023; 41:532-539. [PMID: 36496287 PMCID: PMC9712075 DOI: 10.1016/j.vaccine.2022.11.069] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 11/23/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND Monitoring safety outcomes following COVID-19 vaccination is critical for understanding vaccine safety especially when used in key populations such as elderly persons age 65 years and older who can benefit greatly from vaccination. We present new findings from a nationally representative early warning system that may expand the safety knowledge base to further public trust and inform decision making on vaccine safety by government agencies, healthcare providers, interested stakeholders, and the public. METHODS We evaluated 14 outcomes of interest following COVID-19 vaccination using the US Centers for Medicare & Medicaid Services (CMS) data covering 30,712,101 elderly persons. The CMS data from December 11, 2020 through Jan 15, 2022 included 17,411,342 COVID-19 vaccinees who received a total of 34,639,937 doses. We conducted weekly sequential testing and generated rate ratios (RR) of observed outcome rates compared to historical (or expected) rates prior to COVID-19 vaccination. FINDINGS Four outcomes met the threshold for a statistical signal following BNT162b2 vaccination including pulmonary embolism (PE; RR = 1.54), acute myocardial infarction (AMI; RR = 1.42), disseminated intravascular coagulation (DIC; RR = 1.91), and immune thrombocytopenia (ITP; RR = 1.44). After further evaluation, only the RR for PE still met the statistical threshold for a signal; however, the RRs for AMI, DIC, and ITP no longer did. No statistical signals were identified following vaccination with either the mRNA-1273 or Ad26 COV2.S vaccines. INTERPRETATION This early warning system is the first to identify temporal associations for PE, AMI, DIC, and ITP following BNT162b2 vaccination in the elderly. Because an early warning system does not prove that the vaccines cause these outcomes, more robust epidemiologic studies with adjustment for confounding, including age and nursing home residency, are underway to further evaluate these signals. FDA strongly believes the potential benefits of COVID-19 vaccination outweigh the potential risks of COVID-19 infection.
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Affiliation(s)
- Hui-Lee Wong
- US Food and Drug Administration, Silver Spring, MD, USA
| | | | - Cindy Ke Zhou
- US Food and Drug Administration, Silver Spring, MD, USA
| | - Mao Hu
- Acumen LLC, Burlingame, CA, USA
| | | | | | - Rose Do
- US Food and Drug Administration, Silver Spring, MD, USA
| | | | | | | | | | - Thomas MaCurdy
- Acumen LLC, Burlingame, CA, USA,Department of Economics, Stanford University, Stanford, CA, USA
| | | | | | | | - Steven A. Anderson
- US Food and Drug Administration, Silver Spring, MD, USA,Corresponding author
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