Predictive Model for Adverse Events and Immune Response Based on the Production of Antibodies After the Second-Dose of the BNT162b2 mRNA Vaccine.
BNT162b2 vaccine
adverse effect
antibody
classification and regression tree
Journal
Yonago acta medica
ISSN: 0513-5710
Titre abrégé: Yonago Acta Med
Pays: Japan
ID NLM: 0414002
Informations de publication
Date de publication:
Feb 2022
Feb 2022
Historique:
received:
25
10
2021
accepted:
05
01
2022
entrez:
28
2
2022
pubmed:
1
3
2022
medline:
1
3
2022
Statut:
epublish
Résumé
The BNT162b mRNA vaccine for coronavirus disease 2019, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mimics the immune response to natural infection. Few studies have predicted the adverse effects (AEs) after the second-dose vaccination. We present a predictive model for AEs and immune response after the second-dose of the BNT162b mRNA vaccine. To predict AEs, 282 healthcare workers (HCWs) were enrolled in this prospective observational study. The classification and regression tree (CART) model was established, and its predictive efficacy was assessed. To predict immune response, 282 HCWs were included in the analysis. Moreover, the factors affected by anti-SARS-CoV-2 spike protein RBD antibody (s-IgG) were evaluated using serum samples collected 2 months after the second-dose vaccination. The s-IgG level was assessed using Lumipulse G1200. Multiple regression analyses were conducted to evaluate variables associated with anti-s-IgG titer levels. The most common AEs after the second-dose vaccination were pain (87.6%), redness (17.0%) at the injection site, fatigue (68.8%), headache (53.5%), and fever (37.5%). Based on the CART model, headache after the first-dose vaccination and age < 30 years were identified as the first and second discriminators for predicting the headache after the second-dose vaccination, respectively. In the multiple linear regression model, anti-s-IgG titer levels were associated with age, female sex, and AEs including headache and induration at the injection site after the second-dose vaccination. Headache after the first-dose vaccination can be a predictor of headache after the second-dose vaccination, and AEs are indicators of immune response.
Sections du résumé
BACKGROUND
BACKGROUND
The BNT162b mRNA vaccine for coronavirus disease 2019, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mimics the immune response to natural infection. Few studies have predicted the adverse effects (AEs) after the second-dose vaccination. We present a predictive model for AEs and immune response after the second-dose of the BNT162b mRNA vaccine.
METHODS
METHODS
To predict AEs, 282 healthcare workers (HCWs) were enrolled in this prospective observational study. The classification and regression tree (CART) model was established, and its predictive efficacy was assessed. To predict immune response, 282 HCWs were included in the analysis. Moreover, the factors affected by anti-SARS-CoV-2 spike protein RBD antibody (s-IgG) were evaluated using serum samples collected 2 months after the second-dose vaccination. The s-IgG level was assessed using Lumipulse G1200. Multiple regression analyses were conducted to evaluate variables associated with anti-s-IgG titer levels.
RESULTS
RESULTS
The most common AEs after the second-dose vaccination were pain (87.6%), redness (17.0%) at the injection site, fatigue (68.8%), headache (53.5%), and fever (37.5%). Based on the CART model, headache after the first-dose vaccination and age < 30 years were identified as the first and second discriminators for predicting the headache after the second-dose vaccination, respectively. In the multiple linear regression model, anti-s-IgG titer levels were associated with age, female sex, and AEs including headache and induration at the injection site after the second-dose vaccination.
CONCLUSION
CONCLUSIONS
Headache after the first-dose vaccination can be a predictor of headache after the second-dose vaccination, and AEs are indicators of immune response.
Identifiants
pubmed: 35221761
doi: 10.33160/yam.2022.02.012
pii: 2022.02.012
pmc: PMC8857677
doi:
Types de publication
Journal Article
Langues
eng
Pagination
63-69Informations de copyright
©2022 Tottori University Medical Press.
Déclaration de conflit d'intérêts
The authors declare no conflicts of interest.
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