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Record W4415714560 · doi:10.1016/j.jcvp.2025.100234

Systemic reactogenicity is a correlate of MF59 adjuvant-moderated immunogenicity in influenza vaccinated children

2025· article· en· W4415714560 on OpenAlexaffabout
Charlotte Switzer, Chris P. Verschoor, Eleanor Pullenayegum, Pardeep Singh, Mark Loeb

Bibliographic record

VenueJournal of Clinical Virology Plus · 2025
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsSickKids FoundationUniversity of TorontoMcMaster UniversityHealth Sciences NorthImpact
Fundersnot available
KeywordsReactogenicityImmunogenicityInfluenza vaccineTrivalent influenza vaccineAntibody titerVaccinationAdverse effect

Abstract

fetched live from OpenAlex

Adjuvanted influenza vaccine induces more robust antibody responses, but is associated with more adverse events following vaccination. Prior work has examined the link between vaccine reactions and immunogenicity in adults, but little is known about the association between reactogenicity and postvaccination antibody responses in children, particularly regarding adjuvanted influenza vaccine. This study examines the relationship between reactogenicity and immunogenicity in children vaccinated against influenza, and the immunomodulatory effects of the adjuvant. We conducted a secondary analysis of data from a cluster-randomized trial of children aged 6 to 72 months from Canadian Hutterite colonies. Participants received either a trivalent MF59-adjuvanted vaccine (aTIV) or a quadrivalent non-adjuvanted vaccine (QIV). Reactogenicity was measured using a composite score based on local, systemic, and respiratory reactions recorded within five days post-vaccination. Immunogenicity was assessed by measuring hemagglutination inhibition (HAI) titers before and four weeks after vaccination. Linear mixed models were used to evaluate associations between reactogenicity scores and post-vaccination log-transformed HAI titers. In adjuvanted vaccinees, higher systemic reactogenicity scores were associated with increased antibody titers for A/H1N1 and B/Victoria, relative to nonadjuvanted vaccinees (β: 0.38, 95% CI: 0.17 to 0.60; and (β: 0.44, 95% CI: 0.24 to 0.64 respectively). Higher systemic reactogenicity in nonadjuvanted vaccinees correlated with reduced post-vaccination antibody titers for A/H1N1 (β: -0.36, 95% CI: -0.54 to -0.18) and B/Victoria (β: -0.37, 95% CI: -0.54 to -0.20). Respiratory reactogenicity was positively correlated with immunogenicity in responses to A/H3N2 in the adjuvanted group (β: 0.78, 95% CI: 0.13 to 1.43). Local reactogenicity was associated with A/H1N1 immunogenicity, but showed no significant interaction with vaccine formulation (β: 0.25, 95% CI: 0.04 to 0.47). Systemic reactogenicity in adjuvanted vaccinees showed positive correlations with immunogenicity, whereas reactogenicity contributed to blunting of antibody responses in nonadjuvanted vaccinees. We found that stronger systemic reactions correlate with improved immune responses in the adjuvanted group against all vaccine strains save A/H3N2, which warrants further investigation. Our study finds that reactogenicity is a modest biomarker for vaccine immunogenicity, and that the increased reactogenicity of the adjuvanted vaccine is associated with enhanced immune responsiveness, which may predict greater vaccine effectiveness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.105
GPT teacher head0.478
Teacher spread0.373 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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