Antimalarials are not Effective as Pre-Exposure Prophylaxis for COVID-19: A Retrospective Matched Control Study
August 2023 | Volume 22 | Issue 8 | 840 | Copyright © August 2023
Published online July 31, 2023
Nikokai Klebanov MDa,b*, Vartan Pahalyants MD MBAa,b,c*, Jordan T. Said MDa,b, William. S. Murphy MD MBAa,b,c, Nicholas Theodosakis MD PhDa,b, Joseph Scarry MA, Stacey Duey d, Monina Klevens DDSe, Evelyn Lilly MDa^, Yevgeniy R. Semenov MD MAa^
aMassachusetts General Hospital, Boston, MA
bHarvard Medical School, Boston, MA
cHarvard Business School, Boston, MA
dDivision of Research Information Science and Computing, Mass General Brigham, Boston, MA
eMassachusetts Department of Public Health, Bureau of Infectious Disease, and Laboratory Sciences, Boston, MA
* These authors contributed equally to this manuscript.
^ These authors contributed equally to this manuscript.
Abstract
The early phase of the COVID-19 pandemic prompted a repurposing of antiviral and immunomodulatory drugs as investigational therapeutics, including hydroxychloroquine and chloroquine. While antimalarials have been well-refuted as a treatment for COVID-19, data on these drugs' role in preventing SARS-CoV-2 infection as pre-exposure prophylaxis is more limited. We investigated the efficacy of antimalarial drugs as pre-exposure SARS-CoV-2 prophylaxis in a US tertiary-care center. We identified all adult patients exposed to antimalarials with active prescriptions from July 1, 2019 to February 29, 2020 and exact-matched antimalarial-treated study patients with controls on age, sex, race, and Charleston Comorbidity Index. We used multivariable logistic regression to calculate the odds ratio (OR) of COVID-19 diagnosis by antimalarial exposure, adjusting for demographics, comorbidities, local infection rates, and specific conditions identified in early studies as risk factors for COVID-19. There were 3,074 patients with antimalarial prescriptions and 58,955 matched controls. Hydroxychloroquine represented 98.8% of antimalarial prescriptions. There were 51 (1.7%) infections among antimalarial-exposed and 973 (1.6%) among controls. No protective effect for SARS-CoV-2 infection was demonstrated among antimalarial-exposed patients in the multivariate model (OR=1.06, 95% CI 0.80-1.40, P=0.70). These findings corroborate prior work demonstrating that hydroxychloroquine and related antimalarials do not have a role in protection against SARS-CoV-2.
Klebanov N, Pahalyants V, Said JT, et al. Antimalarials are not effective as pre-exposure prophylaxis for COVID-19: a retrospective matched control study. J Drugs Dermatol. 2023;22(8):840-843. doi:10.36849/JDD.6593
To the editor:
The early phase of the COVID-19 pandemic prompted a repurposing of antiviral and immunomodulatory drugs as investigational therapeutics, including hydroxychloroquine and chloroquine.1 Despite an early interest in these potentially preventative medications given positive in vitro findings,2 randomized control trials of hydroxychloroquine as post-exposure prophylaxis did not reveal differences in infection susceptibility; appropriately, antimalarials are not recommended for treatment of COVID-19.3
While antimalarials have been well-refuted as a treatment for COVID-19, data on these drugs' role in preventing SARS-CoV-2 infection as pre-exposure prophylaxis is more limited. Hydroxychloroquine is frequently prescribed for dermatologic and rheumatologic diseases, and thus data on this drug's pre-exposure impact on SARS-CoV-2 risk is of great importance to the practicing dermatologist. We investigated the efficacy of antimalarial drugs as pre-exposure SARS-CoV-2 prophylaxis in a US tertiary-care center.
MATERIALS AND METHODS
We included all adult patients with at least one prescription for chloroquine, hydroxychloroquine, or quinacrine from July 1, 2019 to February 29, 2020 (limiting prescriptions to those started before the pandemic onset) in the MassGeneral Brigham Enterprise Data Warehouse and Research Patient Data Registry. We exact-matched antimalarial-treated study patients with controls on age, sex, race, and Charleston Comorbidity Index. Additional collected variables included zip codes (used to estimate income using 2010 US Census), and medical history using ICD-9/ICD-10
