Deconstructing the Treatment Effect of Remdesivir in the Adaptive Coronavirus Disease 2019 (COVID-19) Treatment Trial-1: Implications for Critical Care Resource Utilization

• Type of Material: Article
• Authors: Jonathan Fintzi, National Institute of Allergy and Infectious Diseases, Rockville; Tyler Bonnett, Frederick National Laboratory for Cancer Research; Daniel A Sweeney, University of California San Diego; Nikhil A Huprikar, Walter Reed National Military Medical Center; Anuradha Ganesan, Uniformed Services University of Health Sciences; Maria G Frank, University of Colorado, Aurora; Susan LF McLellan, University of Texas Medical Branch, Galveston; Lori E Dodd, National Institute of Allergy and Infectious Diseases; Pablo Tebas, University of Pennsylvania; Aneesh Mehta, Emory University
• Language: English
• Date: 2021-09-16
• Publisher: OXFORD UNIV PRESS INC
• Publication Version: Final Published Version
• Copyright Statement: Published by Oxford University Press for the Infectious Diseases Society of America 2021.
• License: Creative Commons Universal : Public Domain Dedication
• Final Published Version (URL): http://dx.doi.org/10.1093/cid/ciab712
• Title of Journal or Parent Work: CLINICAL INFECTIOUS DISEASES
• Volume: 74
• Issue: 12
• Start Page: 2209
• End Page: 2217
• Grant/Funding Information: The trial has also been funded in part by the governments of Denmark, Japan, Mexico, and Singapore. The trial site in South Korea received funding from the Seoul National University Hospital. Support for the London International Coordinating Centre was also provided by the United Kingdom Medical Research Council (MRC_UU_12023/23).; This analysis used data from the Adaptive COVID-19 Treatment Trial (ACTT-1) trial (DOI:10.1056/NEJMoa2007764). The ACTT-1 trial was sponsored and primarily funded by the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, Maryland. ACTT-1 was funded in part with federal funds from the NIAID and the National Cancer Institute, NIH, under contract HHSN261200800001E 75N910D00024, task order number 75N91019F00130/75N91020F00010, and by the Department of Defense, Defense Health Program. This trial has been supported in part by the NIAID of the NIH under award numbers UM1AI148684, UM1AI148576, UM1AI148573, UM1AI148575, UM1AI148452, UM1AI148685, UM1AI148450, and UM1AI148689.; Collaborating investigators involved with collection of data during the ACTT-1 trial are noted in the Supplementary Appendix. The views expressed are those of the authors and do not reflect the official views of the Uniformed Services University of the Health Sciences, Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., the National Institutes of Health or the Department of Health and Human Services, Walter Reed National Military Medical Center, the Department of Defense, or the Departments of the Army, Navy or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the US Government. This work utilized the computational resources of the NIH HPC Biowulf computing cluster (http://hpc.nih.gov).
• Keywords: MODEL; Science & Technology; critical care; Immunology; Life Sciences & Biomedicine; clinical progression; multistate models; Microbiology; Infectious Diseases; respiratory therapies
• Research Categories: Mathematics; Biology, Biostatistics

Abstract

Background: The Adaptive Coronavirus Disease 2019 (COVID-19) Treatment Trial-1 (ACTT-1) found that remdesivir therapy hastened recovery in patients hospitalized with COVID-19, but the pathway for this improvement was not explored. We investigated how the dynamics of clinical progression changed along 4 pathways: recovery, improvement in respiratory therapy requirement, deterioration in respiratory therapy requirement, and death. Methods: We analyzed trajectories of daily ordinal severity scores reflecting oxygen requirements of 1051 patients hospitalized with COVID-19 who participated in ACTT-1. We developed competing risks models that estimate the effect of remdesivir therapy on cumulative incidence of clinical improvement and deterioration, and multistate models that utilize the entirety of each patient's clinical course to characterize the effect of remdesivir on progression along the 4 pathways above. Results: Based on a competing risks analysis, remdesivir reduced clinical deterioration (hazard ratio [HR], 0.73; 95% confidence interval [CI]:. 59-.91) and increased clinical improvement (HR, 1.22; 95% CI: 1.08, 1.39) relative to baseline. Our multistate models indicate that remdesivir inhibits worsening to ordinal scores of greater clinical severity among patients on room air or low-flow oxygen (HR, 0.74; 95% CI:. 57-.94) and among patients receiving mechanical ventilation or high-flow oxygen/noninvasive positive-pressure ventilation (HR, 0.73; 95% CI:. 53-1.00) at baseline. We also find that remdesivir reduces expected intensive care respiratory therapy utilization among patients not mechanically ventilated at baseline. Conclusions: Remdesivir speeds time to recovery by preventing worsening to clinical states that would extend the course of hospitalization and increase intensive respiratory support, thereby reducing the overall demand for hospital care.