Paxlovid (nirmatrelvir/ritonavir) effectiveness against hospitalization and death in N3C: A target trial emulation study
Year: 2023
Type: preprint
Study design: Observational Study
Abstract: Importance: COVID-19 has placed a monumental burden on the health care system globally. Although no longer a public health emergency, there is still a pressing need for effective treatments to prevent hospitalization and death. Paxlovid (nirmatrelvir/ritonavir) is a promising and potentially effective antiviral that has received emergency use authorization by the U.S. FDA. Objective: Determine real world effectiveness of Paxlovid nationwide and investigate disparities between treated and untreated eligible patients. Design/Setting/Participants: Population-based cohort study emulating a target trial, using inverse probability weighted models to balance treated and untreated groups on baseline confounders. Participants were patients with a SARS-CoV-2 positive test or diagnosis (index) date between December 2021 and February 2023 selected from the National COVID Cohort Collaborative (N3C) database who were eligible for Paxlovid treatment. Namely, adults with at least one risk factor for severe COVID-19 illness, no contraindicated medical conditions, not using one or more strictly contraindicated medications, and not hospitalized within three days of index. From this cohort we identified patients who were treated with Paxlovid within 5 days of positive test or diagnosis (n = 98,060) and patients who either did not receive Paxlovid or were treated outside the 5-day window (n = 913,079 never treated; n = 1,771 treated after 5 days). Exposures: Treatment with Paxlovid within 5 days of positive COVID-19 test or diagnosis. Main Outcomes and Measures: Hospitalization and death in the 28 days following COVID-19 index date. Results: A total of 1,012,910 COVID-19 positive patients at risk for severe COVID-19 were included, 9.7% of whom were treated with Paxlovid. Uptake varied widely by geographic region and timing, with top adoption areas near 50% and bottom near 0%. Adoption increased rapidly after EUA, reaching steady state by 6/2022. Participants who were treated with Paxlovid had a 26% (RR, 0.742; 95% CI, 0.689-0.812) reduction in hospitalization risk and 73% (RR, 0.269, 95% CI, 0.179-0.370) reduction in mortality risk in the 28 days following COVID-19 index date. Conclusions/Relevance: Paxlovid is effective in preventing hospitalization and death in at-risk COVID-19 patients. These results were robust to a large number of sensitivity considerations. Disclosure: The authors report no disclosures. Key points: In Paxlovid-eligible patients, treatment was associated with decreased risk of hospitalization and death. Results align with prior randomized trials and observational studies, thus supporting the real-world effectiveness of Paxlovid.
Source: medRxiv
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: Bill and Melinda Gates Foundation, University of Southern California, University of Nebraska Medical Center, Vanderbilt University, University of Miami, University of Pennsylvania, Ohio State University, Tufts Medical Center, University of Wisconsin-Madison, Northwestern University, Wake Forest University, Vanderbilt Institute for Clinical and Translational Research, University of Chicago, University of Minnesota, University of Michigan, University of Utah, University of Washington, University of Texas Medical Branch, Tulane University, University of Oklahoma, University of Rochester, University of Cincinnati, Pennsylvania State University, University of Arkansas for Medical Sciences, Rush University, Virginia Commonwealth University, Southern California Clinical and Translational Science Institute, Rutgers, The State University of New Jersey, University of Texas Health Science Center at Houston, NorthShore University HealthSystem, Vanderbilt University Medical Center, Institute of Translational Health Sciences, Penn State Clinical and Translational Science Institute, Louisiana Clinical and Translational Science Center, Stony Brook University, University of Illinois at Urbana-Champaign, Institute for Clinical and Translational Research, University of Wisconsin, Madison, Oregon Clinical and Translational Research Institute, University of North Carolina at Chapel Hill, University of Oklahoma Health Sciences Center, University at Buffalo, Michigan Institute for Clinical and Health Research, Leonard M. Miller School of Medicine, Center for Clinical and Translational Research, University of Colorado Denver, Center for Clinical and Translational Science, University of Massachusetts, Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, Translational Research Institute, University of Arkansas for Medical Sciences, South Carolina Clinical and Translational Research Institute, Medical University of South Carolina, Frontiers Clinical and Translational Science Institute, University of Kansas, Colorado Clinical and Translational Sciences Institute, Accelerated Innovation Research Initiative Turning Top Science and Ideas into High-Impact Values
Awards: G1003362385, G1426198371, G1843992630, G2049072053, G210617772, G2152875133, G216896791, G237123860, G2507118478, G2508192175, G2635992203, G2714998049, G2740763107, G3125251562, G3573251375, G3667826151, G4045563614, G4159580532, G4410787187, G4688203610, G476308836, G4811095511, G4823677270, G4851974581, G4852991764, G4900725235, G5049613280, G5059334661, G5086723997, G5159529264, G5286663980, G5352274017, G5385890486, G5409860367, G5430408733, G5555614831, G572024221, G584478153, G5849810213, G6036981074, G625544220, Sage Bionetworks - to evaluate the signs and symptoms of COVID-19 in a data-consortium approach to inform better clinical decision making for diagnosis, G6831857590, G7199445640, G761346317, G7707125228, G8536079613, G8908676624
OpenAlex ID: W4379212296