Is there a Difference in the Immune Response, Efficacy, and Safety of Seasonal Influenza Vaccine in Males and Females? - A Meta-Analysis.

- Data acquisition and extraction:Individual-level data will be requested from the clinical trial registries or other data repository (as relevant) or by contacting the corresponding author on the publication. If authors are not able to provide us individual-level data, but the publication presents results already stratified by sex, we will utilize these aggregate level results. If authors are not able to provide individual-level data, and the publication does not present results already stratified by sex, we will request that the authors re-analyze the data (see data analysis below). Data will be extracted from each study into a table of study characteristics that include: year of publication, study design, primary aim, exposure and outcome definitions, study setting and population, total number of participants, and quality appraisal score. The following study-level data will be extracted/requested when available: sex, age at enrolment, history of previous influenza vaccination (if any), season of influenza vaccination, underlying medical condition. Aggregate values for these characteristics will be obtained when individual-level data is not available. We will also gather outcome data on immunogenicity (HI, MNT), efficacy (laboratory-confirmed influenza and influenza-like illness) and adverse events following immunization (AEFIs)s (local and systemic AEFIs and SAE, and reactogenicity). Additional study-level data extracted will include: assay type used for immunogenicity and laboratory confirmation of infection (including in-house or commercial), vaccine type, dose, season, concurrently administered vaccines, and country. - Data Analysis:1. Stage one: Study-level data analysis:    If the individual-level data are available, we will analyze each study, stratifying on sex and age group (18-49; 50-64; 65 years and over), for the immunogenicity, efficacy and AEFIs of influenza vaccine. Individual-level data for each study will be organized and analyzed based on the outcomes reported (immunogenicity, efficacy and/or safety). If the individual-level data are unavailable/inaccessible for a particular study due to ethical or privacy concerns, and the results were not previous stratified by sex, we will request the authors re-analyze their data and provide us with the aggregated results, stratified by sex and age groups for the outcomes measured in their study. Immunogenicity: We will determine if the immunogenicity of influenza vaccination differs between males and females, by comparing HI and MNT in those vaccinated; stratified by vaccine type, influenza season, dose, and age group. We will not include in this analysis participants who received a placebo or who were not vaccinated. As antibody concentrations (GMT) are usually log-transformed due to their lognormal distribution, we will gather log-transformed data from each study. We will extract the influenza HI and MN antibody titers from original study data following immunization (looking at fold rise and post-vaccine titers). The HI and MN GMT and 95% CI will then be calculated by sex and age groups, as previously defined. For each study, the geometric mean ratio (GMR) comparing male and female groups will be computed from the ratio of the GMTs between the groups. Moreover, the SEM and 95% CI for the GMR will be derived from the log transformed CIs of the GMTs. This will be anti-log transformed to calculate the 95% CI of the GMR. We will then combine the GMRs and report the pooled estimate of the GMR (and 95% CI) for HI and MN. Finally, we will compare the proportions of females vs. males that achieved an antibody response above the correlates of protection. Meta-analysis will be presented as forest plots.•Efficacy: We will compare the efficacy of influenza vaccination for females versus males by comparing the proportion of laboratory-proven influenza infections (by PCR or viral culture) and influenza-like illness in vaccinated vs. unvaccinated individuals, while stratifying by age group, vaccine type, influenza season and dose. The proportions for males versus females will be compared using a two-tailed Z-test.•Safety: We will determine if the proportion of AEFIs and SAEs following influenza vaccination differs between females and males by comparing the proportions of AEFIs and SAEs in those vaccinated and unvaccinated, while stratifying by age group, vaccine type, influenza season and dose. The severity of AEFIs between males and females - as defined in each study, will also be compared. The proportions as well as the severity of AEFIs between males and females will be compared using a two-tailed Z-test.2. Stage two: Meta-analysis of study findings: We will conduct a meta-analysis of the individual study results by sex. We will stratify our analysis by age groups of interest: 18-49 years, 50-64 years, and ≥65 years, season, vaccine type and dose. •Immunogenicity: Data from studies conducted during the same season will be combined. Data will be meta-analyze the results according to each of the influenza strains contained in the vaccines, irrespectively of the vaccine type (i.e. TIV and QIV). We will also conduct a sensitivity analysis in which results will be combined by vaccine type (i.e. TIV and QIV). We will report results by group (i.e. male versus female) stratified by type/dose/route, and season. HI and MNT data will be analyzed separately. • Efficacy: We will use a logistic regression to pool the OR efficacy estimates (VE = 100*(1-OR)) from various studies, and report results by sex while adjusting for vaccine type and season.• Safety: We will report on reactogenicity in females and males, i.e. AEFI and SAE data, as a categorical variable: presence/absence. We will report the proportion of each local reaction (e.g. pain, induration/swelling and erythema/redness), systemic reaction (e.g. fever, myalgia, headache and fatigue) and reported SAEs by group (i.e. male versus female), while stratifying by vaccine type, dose, route and season. We will also pool results for each outcome using binomial regression; the relative risk (RR) for AEFIs and SAEs between females and males will be adjusted for vaccine type and season. Finally, we will assess the presence/absence of publication bias using a funnel plot and Egger test.