z-logo
open-access-imgOpen Access
Bamlanivimab Efficacy in Older and High-BMI Outpatients With COVID-19 Selected for Treatment in a Lottery-Based Allocation Process
Author(s) -
Emily Rubin,
Jonathan Boiarsky,
Lauren Canha,
Anita GiobbieHurder,
Mofei Liu,
Matthew J. Townsend,
Michael Dougan
Publication year - 2021
Publication title -
open forum infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.546
H-Index - 35
ISSN - 2328-8957
DOI - 10.1093/ofid/ofab546
Subject(s) - medicine , odds ratio , context (archaeology) , odds , covid-19 , body mass index , disease , logistic regression , infectious disease (medical specialty) , paleontology , biology
Background Given the challenges associated with timely delivery of monoclonal antibody (mAb) therapy to outpatients with coronavirus disease 2019 (COVID-19) who are most likely to benefit, it is critical to understand the effectiveness of such therapy outside the context of clinical trials. Methods This was a case–control study of 1257 adult outpatients with COVID-19, ≥65 years of age or with body mass index (BMI) ≥35, who were entered into a lottery for mAb therapy. Results Patients who were called to be offered mAb therapy had a statistically significant 44% reduction in the odds of hospitalization within 30 days of a positive severe acute respiratory syndrome coronavirus 2 test compared with those who were not called (odds ratio [OR], 0.56; 95% CI, 0.36–0.89; P=.01). Patients who actually received bamlanivimab had a statistically significant 68% reduction in the odds of hospitalization compared with those who did not receive bamlanivimab (OR, 0.32; 95% CI, 0.11–0.93; P=.04). Conclusions This study supports the effectiveness of bamlanivimab in reducing COVID-19-related hospitalizations in patients ≥65 or with BMI ≥35.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom