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      Mortality risk after COVID-19 vaccination: A self-controlled case series study

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          Abstract

          Background:

          Although previous studies found no-increased mortality risk after COVID-19 vaccination, residual confounding bias might have impacted the findings. Using a modified self-controlled case series (SCCS) design, we assessed the risk of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes after primary series COVID-19 vaccination.

          Methods:

          We analyzed all deaths between December 14, 2020, and August 11, 2021, among individuals from eight Vaccine Safety Datalink sites. Demographic characteristics of deaths in recipients of COVID-19 vaccines and unvaccinated individuals were reported. We conducted SCCS analyses by vaccine type and death outcomes and reported relative incidences (RI). The observation period for death spanned from the dates of emergency use authorization to the end of the study period (August 11, 2021) without censoring the observation period upon death. We pre-specified a primary risk interval of 28-day and a secondary risk interval of 14-day after each vaccination dose. Adjusting for seasonality in mortality analyses is crucial because death rates vary over time. Deaths among unvaccinated individuals were included in SCCS analyses to account for seasonality by incorporating calendar month in the models.

          Results:

          For Pfizer-BioNTech (BNT162b2), RIs of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes were below 1 and 95 % confidence intervals (CIs) excluded 1 across both doses and both risk intervals. For Moderna (mRNA-1273), RI point estimates of all outcomes were below 1, although the 95 % CIs of two RI estimates included 1: cardiac-related (RI = 0.78, 95 % CI, 0.58–1.04) and non-COVID-19 cardiac-related mortality (RI = 0.80, 95 % CI, 0.60–1.08) 14 days after the second dose in individuals without pre-existing cancer and heart disease. For Janssen (Ad26.COV2.S), RIs of four cardiac-related death outcomes ranged from 0.94 to 0.98 for the 14-day risk interval, and 0.68 to 0.72 for the 28-day risk interval and 95 % CIs included 1.

          Conclusion:

          Using a modified SCCS design and adjusting for temporal trends, no-increased risk was found for non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes among recipients of the three COVID-19 vaccines used in the US.

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          Most cited references18

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          Self controlled case series methods: an alternative to standard epidemiological study designs

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            Mortality benefits of influenza vaccination in elderly people: an ongoing controversy.

            Influenza vaccination policy in most high-income countries attempts to reduce the mortality burden of influenza by targeting people aged at least 65 years for vaccination. However, the effectiveness of this strategy is under debate. Although placebo-controlled randomised trials show influenza vaccine is effective in younger adults, few trials have included elderly people, and especially those aged at least 70 years, the age-group that accounts for three-quarters of all influenza-related deaths. Recent excess mortality studies were unable to confirm a decline in influenza-related mortality since 1980, even as vaccination coverage increased from 15% to 65%. Paradoxically, whereas those studies attribute about 5% of all winter deaths to influenza, many cohort studies report a 50% reduction in the total risk of death in winter--a benefit ten times greater than the estimated influenza mortality burden. New studies, however, have shown substantial unadjusted selection bias in previous cohort studies. We propose an analytical framework for detecting such residual bias. We conclude that frailty selection bias and use of non-specific endpoints such as all-cause mortality have led cohort studies to greatly exaggerate vaccine benefits. The remaining evidence base is currently insufficient to indicate the magnitude of the mortality benefit, if any, that elderly people derive from the vaccination programme.
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              Tutorial in biostatistics: the self-controlled case series method.

              The self-controlled case series method was developed to investigate associations between acute outcomes and transient exposures, using only data on cases, that is, on individuals who have experienced the outcome of interest. Inference is within individuals, and hence fixed covariates effects are implicitly controlled for within a proportional incidence framework. We describe the origins, assumptions, limitations, and uses of the method. The rationale for the model and the derivation of the likelihood are explained in detail using a worked example on vaccine safety. Code for fitting the model in the statistical package STATA is described. Two further vaccine safety data sets are used to illustrate a range of modelling issues and extensions of the basic model. Some brief pointers on the design of case series studies are provided. The data sets, STATA code, and further implementation details in SAS, GENSTAT and GLIM are available from an associated website. Copyright 2006 John Wiley & Sons, Ltd.
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                Author and article information

                Journal
                8406899
                7945
                Vaccine
                Vaccine
                Vaccine
                0264-410X
                1873-2518
                8 July 2024
                07 March 2024
                22 February 2024
                11 July 2024
                : 42
                : 7
                : 1731-1737
                Affiliations
                [a ]Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States
                [b ]Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, United States
                [c ]School of Mathematics and Statistics, The Open University, Milton Keynes, UK
                [d ]HealthPartners Institute, Minneapolis, MN, United States
                [e ]Institute for Health Research, Kaiser Permanente Colorado, Denver, CO, United States
                [f ]Department of Epidemiology, University of Colorado School of Public Health, Aurora, CO, United States
                [g ]Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California, Oakland, CA, United States
                [h ]Marshfield Clinic Research Institute, Marshfield, WI, United States
                [i ]Denver Health, Denver, CO, United States
                [j ]Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, United States
                [k ]Acumen LLC, Burlingame, CA, United States
                [l ]Center for Health Research, Kaiser Permanente Northwest, Portland, OR, United States
                [m ]Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, GA, United States
                Author notes
                [* ]Corresponding author at: Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States. Stan.Xu@ 123456kp.org (S. Xu).
                Article
                HHSPA2007681
                10.1016/j.vaccine.2024.02.032
                11238073
                38388239
                ac9c7530-0cd3-434b-b344-207ff5a70a4c

                This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/).

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                Categories
                Article

                Infectious disease & Microbiology
                self-controlled case series,covid-19 vaccines,all-cause mortality,non-covid-19 mortality,cardiac-related mortality

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