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      Analysis of the Effectiveness of the Ad26.COV2.S Adenoviral Vector Vaccine for Preventing COVID-19

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          Key Points

          Question

          How effective is the Ad26.COV2.S adenoviral vector vaccine from Johnson & Johnson at preventing SARS-CoV-2 infection?

          Findings

          This comparative effectiveness research study found that, through large-scale longitudinal retrospective curation of electronic health records from the multistate Mayo Clinic Health System, the Ad26.COV2.S vaccine had an effectiveness of 74%.

          Meaning

          This study suggests that a single dose of the Ad26.COV2.S vaccine appears highly effective at preventing SARS-CoV-2 infection.

          Abstract

          Importance

          Continuous assessment of the effectiveness and safety of the US Food and Drug Administration–authorized SARS-CoV-2 vaccines is critical to amplify transparency, build public trust, and ultimately improve overall health outcomes.

          Objective

          To evaluate the effectiveness of the Johnson & Johnson Ad26.COV2.S vaccine for preventing SARS-CoV-2 infection.

          Design, Setting, and Participants

          This comparative effectiveness research study used large-scale longitudinal curation of electronic health records from the multistate Mayo Clinic Health System (Minnesota, Arizona, Florida, Wisconsin, and Iowa) to identify vaccinated and unvaccinated adults between February 27 and July 22, 2021. The unvaccinated cohort was matched on a propensity score derived from age, sex, zip code, race, ethnicity, and previous number of SARS-CoV-2 polymerase chain reaction tests. The final study cohort consisted of 8889 patients in the vaccinated group and 88 898 unvaccinated matched patients.

          Exposure

          Single dose of the Ad26.COV2.S vaccine.

          Main Outcomes and Measures

          The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts, measured by SARS-CoV-2 polymerase chain reaction testing.

          Results

          The study was composed of 8889 vaccinated patients (4491 men [50.5%]; mean [SD] age, 52.4 [16.9] years) and 88 898 unvaccinated patients (44 748 men [50.3%]; mean [SD] age, 51.7 [16.7] years). The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts was 0.26 (95% CI, 0.20-0.34) (60 of 8889 vaccinated patients vs 2236 of 88 898 unvaccinated individuals), which corresponds to an effectiveness of 73.6% (95% CI, 65.9%-79.9%) and a 3.73-fold reduction in SARS-CoV-2 infections.

          Conclusions and Relevance

          This study’s findings are consistent with the clinical trial–reported efficacy of Ad26.COV2.S and the first retrospective analysis, suggesting that the vaccine is effective at reducing SARS-CoV-2 infection, even with the spread of variants such as Alpha or Delta that were not present in the original studies, and reaffirm the urgent need to continue mass vaccination efforts globally.

          Abstract

          This comparative effectiveness research study used data from the multistate Mayo Clinic Health System to evaluate the effectiveness of the Johnson & Johnson Ad26.COV2.S vaccine at preventing SARS-CoV-2 infection.

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          Most cited references8

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          An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

          The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses.
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            FDA-authorized mRNA COVID-19 vaccines are effective per real-world evidence synthesized across a multi-state health system

            Background Two FDA-authorized mRNA COVID-19 vaccines, BNT162b2 (Pfizer/BioNTech) and mRNA-1273 (Moderna), have demonstrated high efficacies in large Phase 3 randomized clinical trials. It is important to assess their effectiveness in a real-world setting. Methods This is a retrospective analysis of 136,532 individuals in the Mayo Clinic health system (Arizona, Florida, Iowa, Minnesota, Wisconsin) with PCR testing data between December 1, 2020 and April 20, 2021. We compared clinical outcomes for a vaccinated cohort of 68,266 individuals who received at least one dose of either vaccine (n BNT162b2 = 51,795; n mRNA-1273 = 16,471) and an unvaccinated control cohort of 68,266 individuals propensity-matched based on relevant demographic, clinical, and geographic features. We estimated real-world vaccine effectiveness by comparing incidence rates of positive SARS-CoV-2 PCR testing and COVID-19 associated hospitalization and ICU admission starting 7 days after the second vaccine dose. Findings The real-world vaccine effectiveness in preventing SARS-CoV-2 infection was 86.1% (95% CI: 82.4-89.1%) for BNT162b2 and 93.3% (95% CI: 85.7-97.4%) for mRNA-1273. BNT162b2 and mRNA-1273 were 88.8% (95% CI: 75.5-95.7%) and 86.0% (95% CI: 71.6-93.9%) effective in preventing COVID-19 associated hospitalization. Both vaccines were 100% effective (95% CI BNT162b2 : 51.4-100%; 95% CI mRNA-1273 : 43.3-100%) in preventing COVID-19 associated ICU admission. Conclusions BNT162b2 and mRNA-1273 are both effective in a real-world setting and are associated with reduced rates of SARS-CoV-2 infection and decreased burden of COVID-19 on the healthcare system. In this study, Pawlowski et al. assess the real world effectiveness of the BNT162b2 and mRNA-1273 COVID-19 vaccines among 136,532 individuals. They compare infection, hospitalization, and ICU admission rates between vaccinated and propensity matched unvaccinated individuals. They find that both vaccines protect against SARS-CoV-2 infection and severe COVID-19.
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              Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis

              Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVID pos ; n = 2,317) versus COVID-19-negative (COVID neg ; n = 74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVID pos over COVID neg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVID pos patients during the week prior to PCR testing, in addition to anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                2 November 2021
                November 2021
                2 November 2021
                : 4
                : 11
                : e2132540
                Affiliations
                [1 ]nference, Cambridge, Massachusetts
                [2 ]nference Labs, Murgesh Pallya, Bengaluru, Karnataka, India
                [3 ]Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
                Author notes
                Article Information
                Accepted for Publication: September 2, 2021.
                Published: November 2, 2021. doi:10.1001/jamanetworkopen.2021.32540
                Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License. © 2021 Corchado-Garcia J et al. JAMA Network Open.
                Corresponding Authors: Tyler Wagner, PhD ( tyler@ 123456nference.net ), and Venky Soundararajan, PhD ( venky@ 123456nference.net ), nference, One Main St, E Arcade, Cambridge, MA 02142.
                Author Contributions: Dr Soundararajan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Corchado-Garcia and Zemmour are co–first authors.
                Concept and design: Corchado-Garcia, Zemmour, Lenehan, O’Horo, Badley, Halamka, Virk, Swift, Wagner, Soundararajan.
                Acquisition, analysis, or interpretation of data: Corchado-Garcia, Zemmour, Hughes, Bandi, Cristea-Platon, Lenehan, Pawlowski, Bade, O’Horo, Gores, Williams, Badley, Wagner, Soundararajan.
                Drafting of the manuscript: Corchado-Garcia, Zemmour, Hughes, Bade, Soundararajan.
                Critical revision of the manuscript for important intellectual content: Corchado-Garcia, Zemmour, Hughes, Bandi, Cristea-Platon, Lenehan, Pawlowski, O'Horo, Gores, Williams, Badley, Halamka, Virk, Swift, Wagner, Soundararajan.
                Statistical analysis: Corchado-Garcia, Zemmour, Hughes, Bandi, Cristea-Platon, Pawlowski, Bade.
                Obtained funding: Badley.
                Administrative, technical, or material support: Bade, O’Horo, Badley, Soundararajan.
                Supervision: O’Horo, Gores, Badley, Halamka, Wagner, Soundararajan.
                Conflict of Interest Disclosures: Dr Corchado-Garcia reported receiving personal fees from and holding stock in nference Inc outside the submitted work. Dr Zemmour reported receiving personal fees from nference Inc outside the submitted work. Dr Hughes reported receiving personal fees from nference Inc during the conduct of the study; and personal fees from nference Inc outside the submitted work. Mr Lenehan reported receiving other fees from Janssen (nference collaborates with Janssen on data science projects unrelated to this manuscript, and this relationship did not impact the study design or interpretation of its results) outside the submitted work. Dr Pawlowski reported receiving personal fees from nference Inc outside the submitted work. Dr O’Horo reported receiving personal fees from Elsevier and Bates College; and grants from nference Inc, outside the submitted work. Dr Badley reported being a consultant for AbbVie and Gilead; serving on scientific advisory boards for Freedom Tunnel, Pinetree Therapeutics, Primmune, Immunome, Flambeau Diagnostics, nference, and Zentalis; serving on data safety and monitoring boards for Corvus, Equillium, and Excision Biotherapeutics; and being founder and president of Splissen Therapeutics. Dr Virk reported being an inventor for Mayo Clinic Travel App interaction with Smart Medical Kit and Medical Kit for Pilgrims. Dr Swift reported receiving grants from Pfizer during the conduct of the study. Dr Wagner reported receiving personal fees from and holding stock in nference Inc outside the submitted work. Dr Soundararajan reported other from Janssen (nference collaborates with Janssen and other biopharmaceutical companies on data science initiatives unrelated to this study, and these collaborations had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript outside the submitted work. The Mayo Clinic may stand to gain financially from the successful outcome of this research. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and was in compliance with Mayo Clinic Conflict of Interest policies. No other disclosures were reported.
                Additional Information: The data will be made available on reasonable request to the corresponding author. A proposal with detailed description of study objectives and the statistical analysis plan will be needed for evaluation of the reasonability of requests. Deidentified data will be provided after approval from the corresponding author and the Mayo Clinic.
                Article
                zoi210925
                10.1001/jamanetworkopen.2021.32540
                8564583
                34726743
                5fb1d490-52ea-44f9-a6f3-42a2c267172b
                Copyright 2021 Corchado-Garcia J et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY-NC-ND License.

                History
                : 28 April 2021
                : 2 September 2021
                Categories
                Research
                Original Investigation
                Online Only
                Public Health

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