ArticleVaccines2024
Antibody Persistence and Risk of COVID-19 Infection: Insights from Modeling.
Article in Vaccines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05124171 (Immunogenicity and Reactogenicity Following a 3rd Dose of COVID-19 mRNA Vaccine), which is not on this map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Immunogenicity and Reactogenicity Following a 3rd Dose of COVID-19 mRNA Vaccine (Pfizer-BioNtech) and Two Adjuvanted Sub-unit Vaccines (SP/GSK) Administered as a Booster in Adults Who Received 2 Doses of Pfizer-BioNTech mRNA Vaccine as a Primary Vaccination: A Randomized, Single-blinded Multicenter Clinical Trial
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn this post hoc exploratory study of the APHP-COVIBOOST trial (NCT05124171), we used statistical modeling to describe the evolution of neutralizing antibody (nAb) titers over time, asses its impact on SARS-CoV-2 infection, and explore potential differences between three booster vaccine formulations (D614, B.1.351, and BNT162b2).
methodsAntibody titers were measured for 208 adult participants at day 28, 3 months, and 6 months using a microneutralization assay against different Omicron subvariants. We developed four specific Bayesian statistical models based on a core model, accounting for vaccine-specific antibody decline, boosting of nAb for breakthrough infection, and risk of infection according to nAb levels. The model findings were cross-verified using another validated microneutralization assay.
resultsThe decrease in nAb titers was significantly lower for the B.1.351 vaccine than for the other booster formulations. An inverse relationship was found between risk of infection upon exposure and nAb levels. With Omicron BA.1 data, these results translated into a positive relative vaccine efficacy against any infection over 6 months for the B.1.351 vaccine compared to the BNT162b2 (31%) and D614 (21%) vaccines.
conclusionsRisk of infection decreased with increasing nAb titers for all vaccines. Statistical models predicted significantly better antibody persistence for the B.1.351 booster formulation compared to the other evaluated vaccines.
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