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Applicability of probabilistic graphical models for early detection of SARS-CoV-2 reactive antibodies after SARS-CoV-2 vaccination in hematological patients

Authors :
Piñana, José Luis
Rodríguez-Belenguer, Pablo
Caballero, Dolores
Martino, Rodrigo
Lopez-Corral, Lucia
Terol, María-José
Vazquez, Lourdes
Calabuig, Marisa
Sanz-Linares, Gabriela
Marin-Jimenez, Francisca
Alonso, Carmen
Montoro, Juan
Ferrer, Elena
Facal, Ana
Pascual, María-Jesús
Rodriguez-Fernandez, Alicia
Olave, María T
Cascales-Hernandez, Almudena
Gago, Beatriz
Hernández-Rivas, José-Ángel
Villalon, Lucia
Corona, Magdalena
Roldán-Pérez, Alicia
Ribes-Amoros, Julia
González-Santillana, Clara
Garcia-Sanz, Ramon
Navarro, David
Serrano-López, Antonio J
Cedillo, Ángel
Soria-Olivas, Emilio
Sureda, Anna
Solano, Carlos
Infectious Complications Subcommittee of the Spanish Hematopoietic Stem Cell Transplantation and Cell Therapy Group (GETH-TC)
Vanderbilt University
Sociedad Española de Hematología y Hemoterapia
Piñana, José Luis
Piñana, José Luis [0000-0001-8533-2562]
Source :
ANNALS OF HEMATOLOGY, r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA, Consejo Superior de Investigaciones Científicas (CSIC), r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe, instname, r-FISABIO. Repositorio Institucional de Producción Científica, r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau, Digital.CSIC. Repositorio Institucional del CSIC
Publication Year :
2022
Publisher :
SPRINGER, 2022.

Abstract

Prior studies of antibody response after full SARS-CoV-2 vaccination in hematological patients have confirmed lower antibody levels compared to the general population. Serological response in hematological patients varies widely according to the disease type and its status, and the treatment given and its timing with respect to vaccination. Through probabilistic machine learning graphical models, we estimated the conditional probabilities of having detectable anti-SARS-CoV-2 antibodies at 3–6 weeks after SARS-CoV-2 vaccination in a large cohort of patients with several hematological diseases (n= 1166). Most patients received mRNA-based vaccines (97%), mainly Moderna® mRNA-1273 (74%) followed by Pfizer-BioNTech® BNT162b2 (23%). The overall antibody detection rate at 3 to 6 weeks after full vaccination for the entire cohort was 79%. Variables such as type of disease, timing of anti-CD20 monoclonal antibody therapy, age, corticosteroids therapy, vaccine type, disease status, or prior infection with SARS-CoV-2 are among the most relevant conditions influencing SARS-CoV-2-IgG-reactive antibody detection. A lower probability of having detectable antibodies was observed in patients with B-cell non-Hodgkin’s lymphoma treated with anti-CD20 monoclonal antibodies within 6 months before vaccination (29.32%), whereas the highest probability was observed in younger patients with chronic myeloproliferative neoplasms (99.53%). The Moderna® mRNA-1273 compound provided higher probabilities of antibody detection in all scenarios. This study depicts conditional probabilities of having detectable antibodies in the whole cohort and in specific scenarios such as B cell NHL, CLL, MM, and cMPN that may impact humoral responses. These results could be useful to focus on additional preventive and/or monitoring interventions in these highly immunosuppressed hematological patients.<br />REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research. We thank the Spanish Society of Hematology (SEHH) for its support on the study. We sincerely want to thanks the invaluable aid of microbiology services for their commitment in SARS-CoV-2-reactive IgG antibody monitoring in these highly immunosuppressed patients from all participating centers. Finally, we also want to thank the patients, nurses, and study coordinators for their foremost contributions in this study.

Details

ISSN :
09395555
Database :
OpenAIRE
Journal :
ANNALS OF HEMATOLOGY, r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA, Consejo Superior de Investigaciones Científicas (CSIC), r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe, instname, r-FISABIO. Repositorio Institucional de Producción Científica, r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau, Digital.CSIC. Repositorio Institucional del CSIC
Accession number :
edsair.doi.dedup.....b3ee58c62e7825d035489b66d008a3ba