Impact of Prior Season Influenza Vaccination on Seasonal Influenza Vaccine Effectiveness: An Analysis over Four Consecutive Seasons from the Serious Outcomes Surveillance (SOS) Network of the Canadian Immunization Research Network (CIRN)
Notice bibliographique
Résumé
Recent controversy has arisen from observational studies suggesting a potential negative association between prior influenza vaccination and subsequent influenza vaccine effectiveness (VE). As immunologic theories suggest this impact could vary by season/strain, we investigated this association over 4 influenza seasons in Canada. The CIRN SOS Network prospectively enrolled laboratory-confirmed influenza cases and influenza-negative controls admitted to participating hospitals. Using a test-negative control design, matched conditional logistic regression modeling stratifying participants into 4 groups (not vaccinated current or prior season [referent], vaccinated prior season only, vaccinated current season only, and vaccinated both current and prior season) was used to calculate odds ratios (OR) to estimate the effect of vaccination status on influenza-related hospitalization (VE= 1-OR x100). We assessed VE overall and stratified by strain (A/H3N2, A/H1N1, and influenza B) for 4 influenza seasons in Canada: 2011/2012–2014/2015. Although impact of prior vaccination varied, the largest strain-specific impacts were observed in the H3N2 dominant seasons 2012/2013 and 2014/2015, seasons where the H3N2 vaccine component was matched, and mismatched, respectively, to the circulating strain. In 12/13, adjusted VE against influenza H3N2 hospitalization was 58.6% (95% Confidence Interval [CI]: 32.5–74.7%) for patients vaccinated in current season only, relative to 30.9% (10.8–46.5%) among those vaccinated in both prior and current season; VE against influenza B hospitalization in 12/13 was 83.2% (18.9–96.5%) in current season only vaccinees and 54.1% (-6.0–80.2%) in both seasons vaccinees. In 14/15, H3N2 VE was 35.3% (-32.6–68.5%) in current season only vaccinees and -8.3% (-56.7–25.1%) in both seasons vaccinees. While our findings support a possible negative association between prior influenza vaccination and subsequent season VE against some strains in certain seasons, non-statistically significant reductions in VE were observed. Future prospective studies, using varying methodology to examine this association and to explore contributing biological/immunological mechanisms, are critical to inform immunization policy. M. K. Andrew, GSK: Grant Investigator, Research grant; Pfizer: Grant Investigator, Research grant; Sanofi-Pasteur: Grant Investigator, Research grant; T. Hatchette, GSK: Grant Investigator, Grant recipient; Pfizer: Grant Investigator, Grant recipient; Abbvie: Speaker for a talk on biologics and risk of TB reactivation, Speaker honorarium; G. Dos Santos, GSK: Employee, Salary; Business and Decision Life Sciences (Contractor for GSK Vaccines): Independent Contractor, Salary; M. Elsherif, Canadian Institutes of Health Research: Investigator, Research grant; Public Health Agency of Canada: Investigator, Research grant; GSK: Investigator, Research grant; F. Haguinet, GSK: Employee, Salary; J. Mcelhaney, GSK: Scientific Advisor, Honorarium to institution; sanofi pasteur: Scientific Advisor, Honorarium to institution; A. Mcgeer, Hoffman La Roche: Investigator, Research grant; GSK: Investigator, Research grant; sanofi pasteur: Investigator, Research grant; J. Powis, Merck: Grant Investigator, Research grant; GSK: Grant Investigator, Research grant; Roche: Grant Investigator, Research grant; Synthetic Biologicals: Investigator, Research grant; M. Semret, GSK: Investigator, Research grant; Pfizer: Investigator, Research grant; R. Sharma, GSK: Employee and Shareholder, Salary; V. Shinde, Novavax: Employee, Salary; GSK: Shareholder, Stocks; GSK: Employee, Salary; S. Trottier, Canadian Institutes of Health Research: Investigator, Research grant; S. McNeil, GSK: Contract Clinical Trials and Grant Investigator, Research grant; Merck: Contract Clinical Trials and Speaker’s Bureau, Speaker honorarium; Novartis: Contract Clinical Trials, No personal renumeration; sanofi pasteur: Contract Clinical Trials, No personal renumeration
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».