TY - JOUR
T1 - Effect of nirmatrelvir/ritonavir (Paxlovid) on hospitalization among adults with COVID-19
T2 - An electronic health record-based target trial emulation from N3C
AU - N3C Consortium
AU - Bhatia, Abhishek
AU - Preiss, Alexander J.
AU - Xiao, Xuya
AU - Brannock, M. Daniel
AU - Alexander, G. Caleb
AU - Chew, Robert F.
AU - Davis, Hannah
AU - Fitzgerald, Megan
AU - Hill, Elaine
AU - Kelly, Elizabeth P.
AU - Mehta, Hemalkumar B.
AU - Madlock-Brown, Charisse
AU - Wilkins, Kenneth J.
AU - Chute, Christopher G.
AU - Haendel, Melissa
AU - Moffitt, Richard
AU - Pfaff, Emily R.
AU - Wilcox, Adam B.
AU - Lee, Adam M.
AU - Graves, Alexis
AU - Anzalone, Alfred
AU - Manna, Amin
AU - Saha, Amit
AU - Olex, Amy
AU - Zhou, Andrea
AU - Williams, Andrew E.
AU - Southerland, Andrew
AU - Girvin, Andrew T.
AU - Walden, Anita
AU - Sharathkumar, Anjali A.
AU - Amor, Benjamin
AU - Bates, Benjamin
AU - Hendricks, Brian
AU - Patel, Brijesh
AU - Alexander, Caleb
AU - Bramante, Carolyn
AU - Ward-Caviness, Cavin
AU - Madlock-Brown, Charisse
AU - Suver, Christine
AU - Chute, Christopher
AU - Dillon, Christopher
AU - Wu, Chunlei
AU - Schmitt, Clare
AU - Takemoto, Cliff
AU - Housman, Dan
AU - Gabriel, Davera
AU - Eichmann, David A.
AU - Mazzotti, Diego
AU - Brown, Don
AU - Boudreau, Eilis
AU - Hill, Elaine
AU - Zampino, Elizabeth
AU - Marti, Emily Carlson
AU - Pfaff, Emily R.
AU - French, Evan
AU - Koraishy, Farrukh M.
AU - Mariona, Federico
AU - Prior, Fred
AU - Sokos, George
AU - Martin, Greg
AU - Lehmann, Harold
AU - Spratt, Heidi
AU - Mehta, Hemalkumar
AU - Liu, Hongfang
AU - Sidky, Hythem
AU - Hayanga, J. W.Awori
AU - Pincavitch, Jami
AU - Clark, Jaylyn
AU - Harper, Jeremy Richard
AU - Islam, Jessica
AU - Ge, Jin
AU - Gagnier, Joel
AU - Saltz, Joel H.
AU - Saltz, Joel
AU - Loomba, Johanna
AU - Buse, John
AU - Mathew, Jomol
AU - Rutter, Joni L.
AU - McMurry, Julie A.
AU - Guinney, Justin
AU - Starren, Justin
AU - Crowley, Karen
AU - Bradwell, Katie Rebecca
AU - Walters, Kellie M.
AU - Wilkins, Ken
AU - Gersing, Kenneth R.
AU - Cato, Kenrick Dwain
AU - Murray, Kimberly
AU - Kostka, Kristin
AU - Northington, Lavance
AU - Pyles, Lee Allan
AU - Misquitta, Leonie
AU - Cottrell, Lesley
AU - Portilla, Lili
AU - Deacy, Mariam
AU - Bissell, Mark M.
AU - Clark, Marshall
AU - Emmett, Mary
AU - Saltz, Mary Morrison
AU - Palchuk, Matvey B.
AU - Haendel, Melissa A.
AU - Adams, Meredith
AU - Temple-O’Connor, Meredith
AU - Kurilla, Michael G.
AU - Morris, Michele
AU - Qureshi, Nabeel
AU - Safdar, Nasia
AU - Garbarini, Nicole
AU - Sharafeldin, Noha
AU - Sadan, Ofer
AU - Francis, Patricia A.
AU - Burgoon, Penny Wung
AU - Robinson, Peter
AU - Payne, Philip R.O.
AU - Fuentes, Rafael
AU - Jawa, Randeep
AU - Erwin-Cohen, Rebecca
AU - Patel, Rena
AU - Moffitt, Richard A.
AU - Zhu, Richard L.
AU - Kamaleswaran, Rishi
AU - Hurley, Robert
AU - Miller, Robert T.
AU - Pyarajan, Saiju
AU - Michael, Sam G.
AU - Bozzette, Samuel
AU - Mallipattu, Sandeep
AU - Vedula, Satyanarayana
AU - Chapman, Scott
AU - O’Neil, Shawn T.
AU - Setoguchi, Soko
AU - Hong, Stephanie S.
AU - Johnson, Steve
AU - Bennett, Tellen D.
AU - Callahan, Tiffany
AU - Topaloglu, Umit
AU - Sheikh, Usman
AU - Gordon, Valery
AU - Subbian, Vignesh
AU - Kibbe, Warren A.
AU - Hernandez, Wenndy
AU - Beasley, Will
AU - Cooper, Will
AU - Hillegass, William
AU - Zhang, Xiaohan Tanner
N1 - Publisher Copyright:
© 2025 Bhatia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2025/1
Y1 - 2025/1
N2 - Background AU Nirmatrelvir: Pleaseconfirmthatallheadinglevelsarerepresentedcorrectly with ritonavir (Paxlovid) is indicated for patients:with Coronavirus Disease 2019 (COVID-19) who are at risk for progression to severe disease due to the presence of one or more risk factors. Millions of treatment courses have been prescribed in the United States alone. Paxlovid was highly effective at preventing hospitalization and death in clinical trials. Several studies have found a protective association in real-world data, but they variously used less recent study periods, correlational methods, and small, local cohorts. Their estimates also varied widely. The real-world effectiveness of Paxlovid remains uncertain, and it is unknown whether its effect is homogeneous across demographic strata. This study leverages electronic health record data in the National COVID Cohort Collaborative’s (N3C) repository to investigate disparities in Paxlovid treatment and to emulate a target trial assessing its effectiveness in reducing severe COVID-19 outcomes. Methods and findings This target trial emulation used a cohort of 703,647 patients with COVID-19 seen at 34 clinical sites across the United States between April 1, 2022 and August 28, 2023. Treatment was defined as receipt of a Paxlovid prescription within 5 days of the patient’s COVID-19 index date (positive test or diagnosis). To emulate randomization, we used the clone-censor-weight technique with inverse probability of censoring weights to balance a set of covariates including sex, age, race and ethnicity, comorbidities, community well-being index (CWBI), prior healthcare utilization, month of COVID-19 index, and site of care provision. The primary outcome was hospitalization; death was a secondary outcome. We estimated that Paxlovid reduced the risk of hospitalization by 39% (95% confidence interval (CI) [36%, 41%]; p < 0.001), with an absolute risk reduction of 0.9 percentage points (95% CI [0.9, 1.0]; p < 0.001), and reduced the risk of death by 61% (95% CI [55%, 67%]; p < 0.001), with an absolute risk reduction of 0.2 percentage points (95% CI [0.1, 0.2]; p < 0.001). We also conducted stratified analyses by vaccination status and age group. Absolute risk reduction for hospitalization was similar among patients that were vaccinated and unvaccinate, but was much greater among patients aged 65+ years than among younger patients. We observed disparities in Paxlovid treatment, with lower rates among black and Hispanic or Latino patients, and within socially vulnerable communities. This study’s main limitation is that it estimates causal effects using observational data and could be biased by unmeasured confounding. Conclusions In edforthoseusedinthetext this study of Paxlovid’s :Pleaseverifythatallentriesarecorrect real-world effectiveness, : we observed that Paxlovid is effective at preventing hospitalization and death, including among vaccinated patients, and particularly among older patients. This remains true in the era of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron subvariants. However, disparities in Paxlovid treatment rates imply that the benefit of Paxlovid’s effectiveness is not equitably distributed.
AB - Background AU Nirmatrelvir: Pleaseconfirmthatallheadinglevelsarerepresentedcorrectly with ritonavir (Paxlovid) is indicated for patients:with Coronavirus Disease 2019 (COVID-19) who are at risk for progression to severe disease due to the presence of one or more risk factors. Millions of treatment courses have been prescribed in the United States alone. Paxlovid was highly effective at preventing hospitalization and death in clinical trials. Several studies have found a protective association in real-world data, but they variously used less recent study periods, correlational methods, and small, local cohorts. Their estimates also varied widely. The real-world effectiveness of Paxlovid remains uncertain, and it is unknown whether its effect is homogeneous across demographic strata. This study leverages electronic health record data in the National COVID Cohort Collaborative’s (N3C) repository to investigate disparities in Paxlovid treatment and to emulate a target trial assessing its effectiveness in reducing severe COVID-19 outcomes. Methods and findings This target trial emulation used a cohort of 703,647 patients with COVID-19 seen at 34 clinical sites across the United States between April 1, 2022 and August 28, 2023. Treatment was defined as receipt of a Paxlovid prescription within 5 days of the patient’s COVID-19 index date (positive test or diagnosis). To emulate randomization, we used the clone-censor-weight technique with inverse probability of censoring weights to balance a set of covariates including sex, age, race and ethnicity, comorbidities, community well-being index (CWBI), prior healthcare utilization, month of COVID-19 index, and site of care provision. The primary outcome was hospitalization; death was a secondary outcome. We estimated that Paxlovid reduced the risk of hospitalization by 39% (95% confidence interval (CI) [36%, 41%]; p < 0.001), with an absolute risk reduction of 0.9 percentage points (95% CI [0.9, 1.0]; p < 0.001), and reduced the risk of death by 61% (95% CI [55%, 67%]; p < 0.001), with an absolute risk reduction of 0.2 percentage points (95% CI [0.1, 0.2]; p < 0.001). We also conducted stratified analyses by vaccination status and age group. Absolute risk reduction for hospitalization was similar among patients that were vaccinated and unvaccinate, but was much greater among patients aged 65+ years than among younger patients. We observed disparities in Paxlovid treatment, with lower rates among black and Hispanic or Latino patients, and within socially vulnerable communities. This study’s main limitation is that it estimates causal effects using observational data and could be biased by unmeasured confounding. Conclusions In edforthoseusedinthetext this study of Paxlovid’s :Pleaseverifythatallentriesarecorrect real-world effectiveness, : we observed that Paxlovid is effective at preventing hospitalization and death, including among vaccinated patients, and particularly among older patients. This remains true in the era of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron subvariants. However, disparities in Paxlovid treatment rates imply that the benefit of Paxlovid’s effectiveness is not equitably distributed.
UR - http://www.scopus.com/inward/record.url?scp=85216868323&partnerID=8YFLogxK
U2 - 10.1371/journal.pmed.1004493
DO - 10.1371/journal.pmed.1004493
M3 - Article
C2 - 39823513
AN - SCOPUS:85216868323
SN - 1549-1277
VL - 22
JO - PLoS medicine
JF - PLoS medicine
IS - 1
M1 - e1004493
ER -