1973. A Meta-Analysis of the Effectiveness of LAIV4 and IIV against Influenza A/H3N2 Strains in Children 2–18 Years of Age During the 2016–2017 Season
Bibliographic record
Abstract
The effectiveness of the quadrivalent live attenuated influenza vaccine (LAIV4) and inactivated influenza vaccines (IIV) has been evaluated in recent seasons using a number of different study designs (e.g., randomized controlled studies [RCT], cohort studies and test-negative case–control [TNCC] studies). Effectiveness estimates from these studies have, in general, had very broad confidence intervals reflecting the small numbers of cases reported. We conducted a meta-analysis to more precisely estimate the effectiveness of both vaccine types for the 2016–2017 season. LAIV4 and IIV efficacy and effectiveness studies conducted over the 2016–2017 influenza season were identified from the published literature and through personal communication with the study investigators. Effectiveness estimates from all available study designs were included in the meta-analysis to maximize use of all available data and because all studies included methods to minimize bias. The analysis provided average estimates of the LAIV4 and IIV efficacy across countries. A sensitivity analysis limited to TNCC studies was also conducted. Only effectiveness results for A/H3N2 strains were combined as circulation of other strains was minimal. The meta-analyses used a random effects model. Heterogeneity testing was performed. Seven studies conducted in children in the United States, Japan, Finland, Germany, thr UK, and Canada were identified including four TNCC studies, one cohort study and one RCT (Figure 1). Individual effectiveness estimates ranged from 29% to 74% for LAIV4 and from 31% to 56% for IIV. Heterogeneity testing for H3N2 strains was not statistically significant. The consolidated effectiveness estimate across studies for LAIV4 was 44% (95% CI: 24, 58) and for IIV was 45% (95% CI: 29, 58). Estimates for the sensitivity analysis limited to TNCC studies were 61% (95% CI: 40, 74) and 43% (95% CI: 32, 52) for LAIV4 and IIV, respectively. Despite variability in estimates across studies, both LAIV4 and IIV showed moderate and comparable effectiveness in children for circulating H3N2 strains during the 2016–2017 influenza season. R. Mallory, MedImmune: Employee, Salary. A. Bandell, AstraZeneca: Employee, Salary. C. S. Ambrose, AstraZeneca: Employee, Salary. J. Yu, GSK: Employee, Salary and Stockholder.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.069 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".