Abstract

Patients with multiple myeloma (MM), an age-dependent neoplasm of antibody-producing plasma cells, have compromised immune systems and might be at increased risk for severe COVID-19 outcomes. This study characterizes risk factors associated with clinical indicators of COVID-19 severity and all-cause mortality in myeloma patients utilizing NCATS’ National COVID Cohort Collaborative (N3C) database. The N3C consortium is a large, centralized data resource representing the largest multi-center cohort of COVID-19 cases and controls nationwide (>16 million total patients, and >6 million confirmed COVID-19+ cases to date). Our cohort included myeloma patients (both inpatients and outpatients) within the N3C consortium who have been diagnosed with COVID-19 based on positive PCR or antigen tests or ICD-10-CM diagnosis code. The outcomes of interest include all-cause mortality (including discharge to hospice) during the index encounter and clinical indicators of severity (i.e., hospitalization/emergency department/ED visit, use of mechanical ventilation, or extracorporeal membrane oxygenation (ECMO)). Finally, causal inference analysis was performed using the Coarsened Exact Matching (CEM) and Propensity Score Matching (PSM) methods. As of 05/16/2022, the N3C consortium included 1,061,748 cancer patients, out of which 26,064 were MM patients (8,588 were COVID-19 positive). The mean age at COVID-19 diagnosis was 65.89 years, 46.8% were females, and 20.2% were of black race. 4.47% of patients died within 30 days of COVID-19 hospitalization. Overall, the survival probability was 90.7% across the course of the study. Multivariate logistic regression analysis showed histories of pulmonary and renal disease, dexamethasone, proteasome inhibitor/PI, immunomodulatory/IMiD therapies, and severe Charlson Comorbidity Index/CCI were significantly associated with higher risks of severe COVID-19 outcomes. Protective associations were observed with blood-or-marrow transplant/BMT and COVID-19 vaccination. Further, multivariate Cox proportional hazard analysis showed that high and moderate CCI levels, International Staging System (ISS) moderate or severe stage, and PI therapy were associated with worse survival, while BMT and COVID-19 vaccination were associated with lower risk of death. Finally, matched sample average treatment effect on the treated (SATT) confirmed the causal effect of BMT and vaccination status as top protective factors associated with COVID-19 risk among US patients suffering from multiple myeloma. To the best of our knowledge, this is the largest nationwide study on myeloma patients with COVID-19.

Details

Title
Sample average treatment effect on the treated (SATT) analysis using counterfactual explanation identifies BMT and SARS-CoV-2 vaccination as protective risk factors associated with COVID-19 severity and survival in patients with multiple myeloma
Author
Mitra, Amit Kumar 1   VIAFID ORCID Logo  ; Mukherjee, Ujjal Kumar 2   VIAFID ORCID Logo  ; Mazumder, Suman 3 ; Madhira, Vithal 4   VIAFID ORCID Logo  ; Bergquist, Timothy 5 ; Shao, Yu Raymond 6   VIAFID ORCID Logo  ; Liu, Feifan 7 ; Song, Qianqian 8 ; Su, Jing 9   VIAFID ORCID Logo  ; Kumar, Shaji 10   VIAFID ORCID Logo  ; Bates, Benjamin A. 11 ; Sharafeldin, Noha 12 ; Topaloglu, Umit 8 ; Chute, Christopher G. 13 ; Moffitt, Richard A. 14 ; Haendel, Melissa A. 15 

 Auburn University, Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn, USA (GRID:grid.252546.2) (ISNI:0000 0001 2297 8753); Auburn University, Center for Pharmacogenomics and Single-Cell Omics (AUPharmGx), Auburn, USA (GRID:grid.252546.2) (ISNI:0000 0001 2297 8753); UAB Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, USA (GRID:grid.265892.2) (ISNI:0000 0001 0634 4187) 
 University of Illinois, Gies College of Business and Carle Illinois College of Medicine, Urbana-Champaign, USA (GRID:grid.35403.31) (ISNI:0000 0004 1936 9991) 
 Auburn University, Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn, USA (GRID:grid.252546.2) (ISNI:0000 0001 2297 8753); Auburn University, Center for Pharmacogenomics and Single-Cell Omics (AUPharmGx), Auburn, USA (GRID:grid.252546.2) (ISNI:0000 0001 2297 8753) 
 Palila Software LLC, Reno, USA (GRID:grid.252546.2) 
 Sage Bionetworks, Seattle, USA (GRID:grid.430406.5) (ISNI:0000 0004 6023 5303) 
 Duke University Medical Center, Durham, USA (GRID:grid.414179.e) (ISNI:0000 0001 2232 0951) 
 University of Massachusetts Chan Medical School, Worcester, USA (GRID:grid.168645.8) (ISNI:0000 0001 0742 0364) 
 Wake Forest School of Medicine Winston-Salem, Winston-Salem, USA (GRID:grid.241167.7) (ISNI:0000 0001 2185 3318) 
 Indiana University School of Medicine, Department of Biostatistics, Indianapolis, USA (GRID:grid.257413.6) (ISNI:0000 0001 2287 3919) 
10  Department of Internal Medicine, Mayo Clinic, Division of Hematology, Rochester, USA (GRID:grid.417467.7) (ISNI:0000 0004 0443 9942) 
11  Rutgers-RWJMS Medical School, Department of Medicine, New Brunswick, USA (GRID:grid.430387.b) (ISNI:0000 0004 1936 8796) 
12  University of Alabama at Birmingham, School of Medicine, Birmingham, USA (GRID:grid.265892.2) (ISNI:0000000106344187) 
13  Johns Hopkins University, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
14  Stony Brook University, Department of Biomedical Informatics, Stony Brook, USA (GRID:grid.36425.36) (ISNI:0000 0001 2216 9681) 
15  University of Colorado School of Medicine, Center for Health AI, Aurora, USA (GRID:grid.430503.1) (ISNI:0000 0001 0703 675X) 
Pages
180
Publication year
2023
Publication date
Dec 2023
Publisher
Springer Nature B.V.
e-ISSN
20445385
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2898764844
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.