COVID-19 vaccine trials and sex-disaggregated data.
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ABSTRACT:
SUBMITTER: Hussain M
PROVIDER: S-EPMC8726001 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature
Publications
COVID-19 vaccine trials and sex-disaggregated data.
Hussain Musaddique M Fatima Mehwish M Muhammad Iqbal Shahid S Asif Muhammad M Saadullah Malik M Kashif-Ur-Rehman Mukhtar Imran I Ahmad Khan Imran I Parveen Sajida S Fayyaz Tehreem T Shabbir Najia N Kanwal Aisha A Shaukat Saira S Fatima Mobeen M Ikram Nadia N Majeed Abdul A Parveen Farzana F Tariq Muhammad M Barkat Muhammad Qasim MQ Zeng Ling-Hui LH Wu Ximei X
Expert review of vaccines 20211219 3
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Project description:Background Sex and gender are believed to influence vaccine response. Yet, the relationship between sex and gender and COVID-19 vaccine efficacy is poorly understood and remains under-investigated. Methods We conducted a systematic review to determine whether and to what extent post-approval COVID-19 vaccine effectiveness (VE) studies report sex-disaggregated VE data. We searched four publication and pre-publication databases and additional grey literature sources for relevant published/preprint studies released between 1 January 2020 and 1 October 2021 (i.e., pre-Omicron era). We included observational studies providing VE estimates for one or more licensed/approved COVID-19 vaccines and including both males and females. Two reviewers independently assessed study eligibility, extracted data, and assessed risk-of-bias through a modified version of Cochrane’s ROBINS-I tool. A qualitative data synthesis was performed. Results Here we show that, among 240 eligible publications, 68 (28.3%) do not report the sex distribution among participants. Only 21/240 (8.8%) studies provide sex-disaggregated VE estimates, and high between-study heterogeneity regarding design, target population, outcomes, and vaccine type/timing prevent the assessment of sex in determining COVID-19 VE across studies. Conclusions Our findings indicate that few COVID-19 vaccine research publications account for sex. Improved adherence to recommended reporting guidelines will ensure that the evidence generated can be used to better understand the relationship between sex and gender and VE. Plain Language Summary The level of protection that vaccines provide against COVID-19 might depend on a person’s sex or gender. However, sex and gender are not always reported in studies on the effectiveness of COVID-19 vaccines. Here, we systematically reviewed the literature on COVID-19 vaccine effectiveness and looked at whether the studies we found separated out their data on vaccine effectiveness by participants’ sex. Out of the 240 publications we identified, 68 (28.3%) did not report the sex of the participants in their study, and only 21 studies (8.8%) reported vaccine effectiveness data separated by sex. These results show that a substantial proportion of COVID-19 vaccine research publications do not account for sex. Efforts should be made by researchers to study and report the relationship between sex and vaccine effectiveness, to help to optimise vaccination strategies so that all people are adequately protected. Sulis et al. perform a systematic review to investigate to what extent post-approval COVID-19 vaccine effectiveness studies report sex-disaggregated data. They identified 240 relevant publications, of which only a small percentage (8.8%) provided sex-disaggregated effectiveness estimates.
| S-EPMC10196298 | biostudies-literature
Project description:BackgroundSex and gender are crucial variables in coronavirus disease 2019 (COVID-19). We sought to provide information on differences in clinical characteristics and outcomes between male and female patients and to explore the effect of estrogen in disease outcomes in patients with COVID-19.MethodIn this retrospective, multi-center study, we included all confirmed cases of COVID-19 admitted to four hospitals in Hubei province, China from Dec 31, 2019 to Mar 31, 2020. Cases were confirmed by real-time RT-PCR and were analyzed for demographic, clinical, laboratory and radiographic parameters. Random-effect logistic regression analysis was used to assess the association between sex and disease outcomes.ResultsA total of 2501 hospitalized patients with COVID-19 were included in the present study. The clinical manifestations of male and female patients with COVID-19 were similar, while male patients have more comorbidities than female patients. In terms of laboratory findings, compared with female patients, male patients were more likely to have lymphopenia, thrombocytopenia, inflammatory response, hypoproteinemia, and extrapulmonary organ damage. Random-effect logistic regression analysis indicated that male patients were more likely to progress into severe type, and prone to ARDS, secondary bacterial infection, and death than females. However, there was no significant difference in disease outcomes between postmenopausal and premenopausal females after propensity score matching (PSM) by age.ConclusionsMale patients, especially those age-matched with postmenopausal females, are more likely to have poor outcomes. Sex-specific differences in clinical characteristics and outcomes do exist in patients with COVID-19, but estrogen may not be the primary cause. Further studies are needed to explore the causes of the differences in disease outcomes between the sexes.
| S-EPMC8187910 | biostudies-literature
Project description:To speed the development of vaccines against SARS-CoV-2, the United States Federal Government has funded multiple phase 3 trials of candidate vaccines. A single 11-member data and safety monitoring board (DSMB) monitors all government-funded trials to ensure coordinated oversight, promote harmonized designs, and allow shared insights related to safety across trials. DSMB reviews encompass 3 domains: (1) the conduct of trials, including overall and subgroup accrual and data quality and completeness; (2) safety, including individual events of concern and comparisons by randomized group; and (3) interim analyses of efficacy when event-driven milestones are met. Challenges have included the scale and pace of the trials, the frequency of safety events related to the combined enrollment of over 100 000 participants, many of whom are older adults or have comorbid conditions that place them at independent risk of serious health events, and the politicized environment in which the trials have taken place.
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Project description:Experts worldwide have constantly been calling for high-quality open-access epidemiological data, given the fast-evolving nature of the COVID-19 pandemic. Disaggregated high-level granularity records are still scant despite being essential to corroborate the effectiveness of virus containment measures and even vaccination strategies. We provide a complete dataset containing disaggregated epidemiological information about all the COVID-19 patients officially reported during the first 250 days of the COVID-19 pandemic in Bucharest (Romania). We give the sex, age, and the COVID-19 infection confirmation date for 46,440 individual cases, between March 7th and November 11th, 2020. Additionally, we provide context-wise information such as the stringency levels of the measures taken by the Romanian authorities. We procured the data from the local public health authorities and systemized it to respond to the urgent international need of comparing observational data collected from various populations. Our dataset may help understand COVID-19 transmission in highly dense urban communities, perform virus spreading simulations, ascertain the effects of non-pharmaceutical interventions, and craft better vaccination strategies.
| S-EPMC9156663 | biostudies-literature
Project description:COVID-19 has joined the long list of sexually dimorphic human disorders. Higher lethality in men, evident in the first reports from China, was confirmed in the subsequent Italian outbreak. Newspapers and scientific journals commented on this finding and the preexisting conditions, biological processes, and behavioral differences that may underlie it. However, little appeared to be released about sex differences in severity of disease, comorbidities, rate of recovery, length of hospital stay, or number of tests performed. Systematic analysis of official websites for 20 countries and 6 US states revealed a wide disparity in sex-disaggregated data made available to the public and scholars. Only a handful reported cases by sex. None of the other characteristics, including deaths, were stratified by sex at the time. Beyond suboptimal sex disaggregation, we found a paucity of usable raw data sets and a generalized lack of standardization of captured data, making comparisons difficult. A second round of data capture in April found more complete, but even more disparate, information. Our analysis revealed a wide range of sex ratios among confirmed cases. In countries where a male bias was initially reported, the proportion of women dramatically increased in 3 weeks. Analysis also revealed a complex pattern of sex ratio variation with age. Accurate, peer-reviewed, analysis of harmonized, sex-disaggregated data for characteristics of epidemics, such as availability of testing, suspected source of infection, or comorbidities, will be critical to understand where the observed disparities come from and to generate evidence-based recommendations for decision-making by governments.
| S-EPMC7781558 | biostudies-literature
Project description:IntroductionUnderstanding sex and gender differences during outbreaks is critical to delivering an effective response. Although recommendations and minimum requirements exist, the incorporation of sex-disaggregated data and gender analysis into outbreak analytics and response for informed decision-making remains infrequent. A scoping review was conducted to provide an overview of the extent of sex-disaggregated data and gender analysis in outbreak response within low- and middle-income countries (LMICs).MethodsFive databases were searched for peer-reviewed literature examining sex- and gender-specific outcomes for communicable disease outbreaks published in English between 1 January 2012 and 12 April 2022. An adapted version of the WHO's Gender Analysis Matrix was used to synthesise evidence, which was then mapped across four phases of the outbreak timeline: prevention, detection, treatment/management and recovery.Results71 articles met inclusion criteria and were included in this review. Sex-, gender-, and pregnancy-related disparities were identified throughout all four phases of the outbreak timeline. These disparities encompassed a wide range of risk factors for disease, vulnerability, access to and use of services, health-seeking behaviour, healthcare options, as well as experiences in healthcare settings and health and social outcomes and consequences.ConclusionSignificant gender-evidence gaps remain in outbreak response. Evidence that is available illustrates that sex and gender disparities in outbreaks vary by disease, setting and population, and these differences play significant roles in shaping outbreak dynamics. As such, failing to collect, analyse or use sex-disaggregated data and gendered data during outbreaks results in less effective responses, differential adverse health outcomes, increased vulnerability among certain groups and insufficient evidence for effective prevention and response efforts. Systematic sex- and gender-based analyses to ensure gender-responsive outbreak prevention, detection, treatment/management and recovery are urgently needed.
| S-EPMC11749539 | biostudies-literature
Project description:In the last two years, the coronavirus disease 19 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a scientific and social challenge worldwide. Vaccines have been the most effective intervention for reducing virus transmission and disease severity. However, virus genetic variants are still circulating among vaccinated individuals with different symptomatology disease cases. Understanding the protective or disease associated mechanisms in vaccinated individuals is relevant to advance in vaccine development and implementation. To address this objective, serum protein profiles were characterized by quantitative proteomics and data analysis algorithms in four cohorts of vaccinated individuals uninfected and SARS-CoV-2 infected with asymptomatic, nonsevere and severe disease symptomatology. The results showed that immunoglobulins were the most overrepresented proteins in infected cohorts when compared to PCR-negative individuals. The immunoglobulin profile varied between different infected cohorts and correlated with protective or disease associated capacity. Overrepresented immunoglobulins in PCR-positive individuals correlated with protective response against SARS-CoV-2, other viruses, and thrombosis in asymptomatic cases. In nonsevere cases, correlates of protection against SARS-CoV-2 and HBV together with risk of myasthenia gravis and allergy and autoantibodies were observed. Patients with severe symptoms presented risk for allergy, chronic idiopathic thrombocytopenic purpura, and autoantibodies. The analysis of underrepresented immunoglobulins in PCR-positive compared to PCR-negative individuals identified vaccine-induced protective epitopes in various coronavirus proteins including the Spike receptor-binding domain RBD. Non-immunoglobulin proteins were associated with COVID-19 symptoms and biological processes. These results evidence host-associated differences in response to vaccination and the possibility of improving vaccine efficacy against SARS-CoV-2.
2022-10-14 | PXD031969 | Pride
Project description:Severe adverse events (AEs) after COVID-19 vaccination are not well studied in randomized controlled trials (RCTs) due to rarity and short follow-up. To monitor the safety of COVID-19 vaccines ("Pfizer" vaccine dose 1 and 2, "Moderna" vaccine dose 1 and 2, and "Janssen" vaccine single dose) in the U.S., especially regarding severe AEs, we compare the relative rankings of these vaccines using both RCT and the Vaccine Adverse Event Reporting System (VAERS) data. The risks of local and systemic AEs were assessed from the three pivotal COVID-19 vaccine trials and also calculated in the VAERS cohort consisting of 559,717 reports between December 14, 2020 and September 17, 2021. AE rankings of the five vaccine groups calculated separately by RCT and VAERS were consistent, especially for systemic AEs. For severe AEs reported in VAERS, the reported risks of thrombosis and GBS after Janssen vaccine were highest. The reported risk of shingles after the first dose of Moderna vaccine was highest, followed by the second dose of the Moderna vaccine. The reported risk of myocarditis was higher after the second dose of Pfizer and Moderna vaccines. The reported risk of anaphylaxis was higher after the first dose of Pfizer vaccine. Limitations of this study are the inherent biases of the spontaneous reporting system data, and only including three pivotal RCTs and no comparison with other active vaccine safety surveillance systems.
| S-EPMC9243073 | biostudies-literature
Project description:The SARS-CoV-2 Delta (B.1.617.2) variant is capable of infecting vaccinated persons. An open question remains as to whether deficiencies in specific vaccine-elicited immune responses result in susceptibility to vaccine breakthrough infection. We investigated 55 vaccine breakthrough infection cases (mostly Delta) in Singapore, comparing them against 86 vaccinated close contacts who did not contract infection. Vaccine breakthrough cases showed lower memory B cell frequencies against SARS-CoV-2 receptor binding domain (RBD). Compared to plasma antibodies, antibodies secreted by memory B cells retained a higher fraction of neutralizing properties against the Delta variant. Inflammatory cytokines including IL-1β and TNF were lower in vaccine breakthrough infections than primary infection of similar disease severity, underscoring the usefulness of vaccination in preventing inflammation. This report highlights the importance of memory B cells against vaccine breakthrough, and suggests that lower memory B cell levels may be a correlate of risk for Delta vaccine breakthrough infection.
| S-SCDT-EMM-2021-15227 | biostudies-other
Project description:BackgroundThe results and data availability of vaccine trials directly affect the decisions of healthcare providers, the public, and policymakers as to whether the vaccine should be applied. However, the reporting and data sharing level of COVID-19 vaccine studies are not clear.MethodsA cross-sectional study was conducted. A systematic search up to 9 May 2021 in 12 databases and an updated search to 6 July 2021 were conducted in the Cochrane Living Systematic Review and Network Meta-Analysis database to identify COVID-19 vaccine trials. The basic characteristics of included trials were summarized. The reporting level was assessed according to the CONSORT checklist. The data sharing level was assessed by open science practices. Types of incomplete reporting including protocol deviation, lack of primary outcomes clarity, and the omission of harms were analyzed.FindingsFinally, thirty-six COVID-19 vaccine articles reporting on 40 randomized controlled trials were included in this analysis. Based on the CONSORT checklist, the mean reporting score was 29.7 [95% confidence interval 28.7, 30.7]. Thirty-one articles (31/36, 86.1%) had data sharing statements, twenty-five articles (25/36, 69.4%) provided access to the source data. Twenty-seven articles (27/36, 75.0%) had protocol deviation, lack of primary outcomes clarity, or the omission of harms.InterpretationThe reporting and data sharing level of COVID-19 vaccine trials were not optimal. We hope that the reporting and data sharing of future trials will be improved. We recommend establishing a comprehensive, accurate data sharing system for future vaccine trials.FundingThis work was supported by the National Key R&D Program of China (2019YFC1710400; 2019YFC1710403).
| S-EPMC8947811 | biostudies-literature