Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: an EHR-based Target Trial Emulation from N3C

Abstract

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 COVID-19 hospitalization rates. From an eligible population of 632,822 COVID-19 patients seen at 33 clinical sites across the United States between December 23, 2021 and December 31, 2022, patients were matched across observed treatment groups, yielding an analytical sample of 410,642 patients patients. We estimate a 65% reduced odds of hospitalization among Paxlovid-treated patients within a 28-day follow-up period, and this effect did not vary by patient vaccination status. Notably, we observe disparities in Paxlovid treatment, with lower rates among Black and Hispanic or Latino patients, and within socially vulnerable communities. Ours is the largest study of Paxlovid's real-world effectiveness to date, and our primary findings are consistent with previous randomized control trials and real-world studies.

Effectiveness of nirmatrelvir‐ritonavir on severe outcomes of COVID‐19 in the era of vaccination and Omicron: An updated meta‐analysis

“…Of the 32 included studies, 14 offered effect estimates separated by vaccination status. Definition of fully vaccinated patients differed by study; some studies offered data for basic vaccination (two doses or one dose of the vaccine by Johnson & Johnson) and boosted patients (received ≥3 doses or the Johnson & Johnson vaccine + ≥1 booster dose), 20,34–36,43,45,55,57,58,61,63 others merged the group of basic vaccination and boosted patients (received ≥2 doses) 39,46,47 . These differences between studies may be due to differences in vaccination timelines across countries, with some countries having had earlier access to vaccination than others.…”

“…The results are found in Supporting Information S1: Table . The NNT ranges from 48 to prevent one hospitalization or death, based on a reported incidence of 4.51%, 63 to 426 to prevent 1 hospitalization, based on an incidence of 0.51% of severe covid‐19 or death 39 . The largest among these studies, 58 with a vaccination coverage of 75%, reported an incidence of 0.86% risk of hospitalization among high‐risk patients, which in combination with our pooled RR for hospitalization (RR: 0.43) translated to a NNT of 204.…”

“…There was no evidence of publication bias for mortality, dose), 20,[34][35][36]43,45,55,57,58,61,63 others merged the group of basic vaccination and boosted patients (received ≥2 doses). 39,46,47 These differences between studies may be due to differences in vaccination timelines across countries, with some countries having had earlier access to vaccination than others. Therefore, separate analysis of boosted patients may not have been possible due to small sample size in some study populations.…”

Making causal inferences from transactional data: A narrative review of opportunities and challenges when implementing the target trial framework

“…The target trial framework can be used to design studies that address a wide range of research questions, including ones related to drug safety, treatment effectiveness, or disease prognosis. 20–40 However, we can only emulate pragmatic target trials because real-world data cannot be used to emulate a placebo-controlled trial or, one that employs a blinded design. 2…”

“…Examples of this include direct comparisons between different vaccine products and regimens, 20–24 as well as estimation of the effects of glucose-lowering drugs on diverse health outcomes. 25–27 In addition, these data have been used in the assessment of the impact of various monoclonal antibodies on asthma, 28 evaluation of the influence of multiple antiviral agents on hospital admissions in SARS-CoV-2 patients, 29–31 and in the comparison of benzodiazepine regimens in individuals with post-traumatic stress disorder (PTSD). 32 Furthermore, investigations within this domain have also encompassed analysis of dosing and treatment timing.…”