Relative Effectiveness of the Cell-Cultured Quadrivalent Influenza Vaccine Compared to Standard, Egg-derived Quadrivalent Influenza Vaccines in Preventing Influenza-like Illness in 2017–2018
Bibliographic record
Abstract
BACKGROUND: Influenza antigens may undergo adaptive mutations during egg-based vaccine production. In the 2017-2018 influenza season, quadrivalent, inactivated cell-derived influenza vaccine (ccIIV4) vaccine was produced using A(H3N2) seed virus propagated exclusively in cell culture, thus lacking egg adaptive changes. This United States study estimated relative vaccine effectiveness (rVE) of ccIIV4 vs egg-derived quadrivalent vaccines (egg-derived IIV4) for that season. METHODS: Vaccination, outcome, and covariate data were ascertained retrospectively from a electronic medical record (EMR) dataset and analyzed. The study cohort included patients ≥ 4 years of age. rVE was estimated against influenza-like illness (ILI) using diagnostic International Classification of Diseases, Ninth or Tenth Revision codes. The adjusted odds ratios used to derive rVE estimates were estimated from multivariable logistic regression models adjusted for age, sex, race/ethnicity, geographic region, and health status. RESULTS: Overall, 92 187 individuals had a primary care EMR record of ccIIV4 and 1 261 675 had a record of egg-derived IIV4. In the ccIIV4 group, 1705 narrowly defined ILI events occurred, and 25 645 occurred in the standard egg-derived IIV4 group. Crude rVE was 9.2% (95% confidence interval [CI], 4.6%-13.6%). When adjusted for age, sex, health status, comorbidities, and geographic region, the estimated rVE changed to 36.2% (95% CI, 26.1%-44.9%). CONCLUSIONS: ccIIV4, derived from A(H3N2) seed virus propagated exclusively in cell culture, was more effective than egg-derived IIV4 in preventing ILI during the 2017-2018 influenza season. This result suggests that cell-derived influenza vaccines may have greater effectiveness than standard egg-derived vaccines.
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How this classification was reachedexpand
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".