The Influence of Social Determinants on Receiving Outpatient Treatment with Monoclonal Antibodies, Disease Risk, and Effectiveness for COVID-19.
COVID-19
disease risk
effectiveness
monoclonal antibodies
social determinants of health
treatment
Journal
Journal of general internal medicine
ISSN: 1525-1497
Titre abrégé: J Gen Intern Med
Pays: United States
ID NLM: 8605834
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
received:
27
01
2023
accepted:
05
07
2023
pmc-release:
01
12
2024
pubmed:
16
9
2023
medline:
16
9
2023
entrez:
15
9
2023
Statut:
ppublish
Résumé
Limited research has studied the influence of social determinants of health (SDoH) on the receipt, disease risk, and subsequent effectiveness of neutralizing monoclonal antibodies (nMAbs) for outpatient treatment of COVID-19. To examine the influence of SDoH variables on receiving nMAb treatments and the risk of a poor COVID-19 outcome, as well as nMAb treatment effectiveness across SDoH subgroups. Retrospective observational study utilizing electronic health record data from four health systems. SDoH variables analyzed included race, ethnicity, insurance, marital status, Area Deprivation Index, and population density. COVID-19 patients who met at least one emergency use authorization criterion for nMAb treatment. We used binary logistic regression to examine the influence of SDoH variables on receiving nMAb treatments and risk of a poor outcome from COVID-19 and marginal structural models to study treatment effectiveness. The study population included 25,241 (15.1%) nMAb-treated and 141,942 (84.9%) non-treated patients. Black or African American patients were less likely to receive treatment than white non-Hispanic patients (adjusted odds ratio (OR) = 0.86; 95% CI = 0.82-0.91). Patients who were on Medicaid, divorced or widowed, living in rural areas, or living in areas with the highest Area Deprivation Index (most vulnerable) had lower odds of receiving nMAb treatment, but a higher risk of a poor outcome. For example, compared to patients on private insurance, Medicaid patients had 0.89 (95% CI = 0.84-0.93) times the odds of receiving nMAb treatment, but 1.18 (95% CI = 1.13-1.24) times the odds of a poor COVID-19 outcome. Age, comorbidities, and COVID-19 vaccination status had a stronger influence on risk of a poor outcome than SDoH variables. nMAb treatment benefited all SDoH subgroups with lower rates of 14-day hospitalization and 30-day mortality. Disparities existed in receiving nMAbs within SDoH subgroups despite the benefit of treatment across subgroups.
Sections du résumé
BACKGROUND
BACKGROUND
Limited research has studied the influence of social determinants of health (SDoH) on the receipt, disease risk, and subsequent effectiveness of neutralizing monoclonal antibodies (nMAbs) for outpatient treatment of COVID-19.
OBJECTIVE
OBJECTIVE
To examine the influence of SDoH variables on receiving nMAb treatments and the risk of a poor COVID-19 outcome, as well as nMAb treatment effectiveness across SDoH subgroups.
DESIGN
METHODS
Retrospective observational study utilizing electronic health record data from four health systems. SDoH variables analyzed included race, ethnicity, insurance, marital status, Area Deprivation Index, and population density.
PARTICIPANTS
METHODS
COVID-19 patients who met at least one emergency use authorization criterion for nMAb treatment.
MAIN MEASURE
METHODS
We used binary logistic regression to examine the influence of SDoH variables on receiving nMAb treatments and risk of a poor outcome from COVID-19 and marginal structural models to study treatment effectiveness.
RESULTS
RESULTS
The study population included 25,241 (15.1%) nMAb-treated and 141,942 (84.9%) non-treated patients. Black or African American patients were less likely to receive treatment than white non-Hispanic patients (adjusted odds ratio (OR) = 0.86; 95% CI = 0.82-0.91). Patients who were on Medicaid, divorced or widowed, living in rural areas, or living in areas with the highest Area Deprivation Index (most vulnerable) had lower odds of receiving nMAb treatment, but a higher risk of a poor outcome. For example, compared to patients on private insurance, Medicaid patients had 0.89 (95% CI = 0.84-0.93) times the odds of receiving nMAb treatment, but 1.18 (95% CI = 1.13-1.24) times the odds of a poor COVID-19 outcome. Age, comorbidities, and COVID-19 vaccination status had a stronger influence on risk of a poor outcome than SDoH variables. nMAb treatment benefited all SDoH subgroups with lower rates of 14-day hospitalization and 30-day mortality.
CONCLUSION
CONCLUSIONS
Disparities existed in receiving nMAbs within SDoH subgroups despite the benefit of treatment across subgroups.
Identifiants
pubmed: 37715096
doi: 10.1007/s11606-023-08324-y
pii: 10.1007/s11606-023-08324-y
pmc: PMC10713505
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
3472-3481Subventions
Organisme : Administration for Strategic Preparedness and Response
ID : Contract Number 75FCMC18D0047 Task Order 75A50121F80012
Informations de copyright
© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.
Références
PLoS One. 2020 Dec 9;15(12):e0242953
pubmed: 33296357
J Prim Care Community Health. 2021 Jan-Dec;12:21501327211019282
pubmed: 34032171
Ann Intern Med. 2021 May;174(5):698-700
pubmed: 33556271
PLoS One. 2020 Aug 11;15(8):e0237419
pubmed: 32780765
Lancet Reg Health Am. 2022 Mar;7:100138
pubmed: 34901919
J Acquir Immune Defic Syndr. 2021 Feb 1;86(2):200-207
pubmed: 33196555
JAMA Netw Open. 2022 Oct 3;5(10):e2238507
pubmed: 36282499
JAMA Netw Open. 2021 Jul 1;4(7):e2116901
pubmed: 34255046
Mayo Clin Proc. 2021 May;96(5):1250-1261
pubmed: 33958056
Mayo Clin Proc. 2022 Jan;97(1):26-30
pubmed: 34996562
MMWR Morb Mortal Wkly Rep. 2022 Jan 21;71(3):96-102
pubmed: 35051133
N Engl J Med. 2018 Jun 28;378(26):2456-2458
pubmed: 29949490
JAMA. 2015 Aug 11;314(6):555-6
pubmed: 26262792
J Gen Intern Med. 2022 Aug;37(10):2505-2513
pubmed: 35469360
PLoS One. 2022 Mar 3;17(3):e0261508
pubmed: 35239664
MMWR Morb Mortal Wkly Rep. 2022 Oct 28;71(43):1359-1365
pubmed: 36301738
J Clin Epidemiol. 2013 Aug;66(8 Suppl):S84-S90.e1
pubmed: 23849158
Pharmacoepidemiol Drug Saf. 2011 Nov;20(11):1115-29
pubmed: 21805529