Sex Differences in the Immunogenicity and Efficacy of Seasonal Influenza Vaccines: A Meta-analysis of Randomized Controlled Trials
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Bibliographic record
Abstract
Abstract Background Sex impacts individuals’ response to vaccination. However, most vaccine studies do not report these differences disaggregated by sex. The aim of this study was to assess sex differences in the immunogenicity and efficacy of influenza vaccine. Methods We performed a meta-analysis using phase 3 randomized controlled trial data conducted between 2010 and 2018. Using hemagglutination inhibition antibody titers for each strain, differences in geometric mean ratios (GMRs) were calculated by sex. Risk ratios (RRs) comparing seroconversion proportions were pooled for females and males using random-effects models. Vaccine efficacy (VE) was assessed. Data were analyzed by age group (18–64 vs ≥65 years). Results A total of 33 092 healthy adults from 19 studies were included for immunogenicity analysis, and 6740 from 1 study for VE. Whereas no sex differences in immunogenicity were found in adults <65 years old, older females had a significantly greater chance to seroconvert compared to older males for all strains: RRH1N1 = 1.17 [95% confidence interval {CI}, 1.12–1.23]; RRH3N2 = 1.09 [95% CI, 1.05–1.14]; RRVictoria = 1.23 [95% CI, 1.14–1.31]; RRYamagata = 1.22 [95% CI, 1.14–1.30]. GMRs were also higher in older females for all strains compared to older males. VE in preventing laboratory-confirmed influenza was higher in older females compared to older males with VEs of 27.32% (95% CI, 1.15%–46.56%) and 6.06% (95% CI, −37.68% to 35.90%), respectively. Conclusions Our results suggest a higher immunogenicity and VE in females compared to males in older adults. These differences in immunogenicity and VE support the disaggregation of vaccine data by sex in clinical trials and observational studies. Clinical Trials Registration CRD42018112260.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it