Early identification of high-risk individuals for monoclonal antibody therapy and prophylaxis is feasible by SARS-CoV-2 anti-spike antibody specific lateral flow assay.
COVID-19
Lateral flow assay
Monoclonal antibody
Journal
Diagnostic microbiology and infectious disease
ISSN: 1879-0070
Titre abrégé: Diagn Microbiol Infect Dis
Pays: United States
ID NLM: 8305899
Informations de publication
Date de publication:
Nov 2022
Nov 2022
Historique:
received:
10
06
2022
revised:
17
07
2022
accepted:
06
08
2022
pubmed:
10
9
2022
medline:
12
10
2022
entrez:
9
9
2022
Statut:
ppublish
Résumé
Monoclonal antibody therapy has been approved for prophylaxis and treatment of severe COVID-19 infection. Greatest benefit appears limited to those yet to mount an effective immune response from natural infection or vaccination, but concern exists around ability to make timely assessment of immune status of community-based patients where laboratory-based serodiagnostics predominate. Participants were invited to undergo paired laboratory-based (Abbott Architect SARS-CoV-2 IgG Quant II chemiluminescent microparticle immunoassay) and lateral flow assays (LFA; a split SARS-CoV-2 IgM/IgG and total antibody test) able to detect SARS-CoV-2 anti-spike antibodies. LFA band strength was compared with CMIA titer by log-linear regression. Two hundred individuals (median age 43.5 years, IQR 30-59; 60.5% female) underwent testing, with a further 100 control sera tested. Both LFA band strengths correlated strongly with CMIA antibody titers (P < 0.001). LFAs have the potential to assist in early identification of seronegative patients who may demonstrate the greatest benefit from monoclonal antibody treatment.
Identifiants
pubmed: 36084423
pii: S0732-8893(22)00154-7
doi: 10.1016/j.diagmicrobio.2022.115788
pmc: PMC9371766
pii:
doi:
Substances chimiques
Antibodies, Monoclonal
0
Antibodies, Viral
0
Immunoglobulin G
0
Immunoglobulin M
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
115788Informations de copyright
Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.
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