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

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.

• Authors: José Luis Piñana, Pablo Rodríguez-Belenguer, Dolores Caballero, Rodrigo Martino, Lucia Lopez-Corral, María-José Terol, Lourdes Vazquez, Marisa Calabuig, Gabriela Sanz-Linares, Francisca Marin-Jimenez, Carmen Alonso, Juan Montoro, Elena Ferrer, Ana Facal, María-Jesús Pascual, Alicia Rodriguez-Fernandez, María T Olave, Almudena Cascales-Hernandez, Beatriz Gago, José-Ángel Hernández-Rivas, Lucia Villalon, Magdalena Corona, Alicia Roldán-Pérez, Julia Ribes-Amoros, Clara González-Santillana, Ramon Garcia-Sanz, David Navarro, Antonio J Serrano-López, Ángel Cedillo, Emilio Soria-Olivas, Anna Sureda, Carlos Solano, Infectious Complications Subcommittee of the Spanish Hematopoietic Stem Cell Transplantation and Cell Therapy Group (GETH-TC)
• Journal: Annals of hematology (Ann Hematol) Vol. 101 Issue 9 Pg. 2053-2067 (Sep 2022) ISSN: 1432-0584 [Electronic] Germany
• PMID: 35780254 (Publication Type: Journal Article)
• Copyright: © 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Chemical References

• Antibodies, Monoclonal
• Antibodies, Viral
• Antineoplastic Agents
• COVID-19 Vaccines
• BNT162 Vaccine

Topics

• Antibodies, Monoclonal
• Antibodies, Viral
• Antineoplastic Agents
• BNT162 Vaccine
• COVID-19 (diagnosis, prevention & control)
• COVID-19 Vaccines
• Early Detection of Cancer
• Humans
• SARS-CoV-2
• Vaccination