COVID-19 rebound after Paxlovid treatment during Omicron BA.5 vs BA.2.12.1 subvariant predominance period

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Abstract

Paxlovid was authorized by FDA to treat mild-to-moderate COVID-19. In May 2022, the Centers for Disease Control and Prevention (CDC) issued a Health Alert Network Health Advisory on potential COVID-19 rebound after Paxlovid treatment. Since June 2022, Omicron BA.5 has become the dominant subvariant in the US, which is more resistant to neutralizing antibodies than the previous subvariant BA.2.12.1. Questions remain as to how COVID-19 rebound after Paxlovid treatment differs between the BA.5 and BA.2.12.1 subvariants. This is a retrospective cohort study of 15,913 patients who contracted COVID-19 between 5/8/2022–7/18/2022 and were prescribed Paxlovid within 5 days of their COVID-19 infection. The study population was divided into 2 cohorts: (1) BA.5 cohort (n=5,161) – contracted COVID-19 during 6/19/22–7/18/22 when BA.5 was the predominant subvariant ². (2) BA.2.12.1 cohort (n=10,752) – contracted COVID-19 during 5/8/22–6/18/22 when the BA.2.12.1 was the predominant subvariant. The risks of both COVID-19 rebound infections and symptoms 2–8 days after Paxlovid treatment were higher in the BA.5 cohort than in the propensity-score matched BA.2.12.1 cohort: rebound infections (Hazard Ratio or HR: 1.32, 95% CI: 1.06–1.66), rebound symptoms (HR: 1.32, 95% CI: 1.04–1.68). As SARS-CoV-2 evolves with successive subvariants more evasive to antibodies, continuous vigilant monitoring is necessary for COVID-19 rebounds after Paxlovid treatment and longer time duration of Paxlovid treatment warrants evaluation.

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Antibody evasion by SARS-CoV-2 Omicron subvariants BA.2.12.1, BA.4 and BA.5

Qian Wang, Yicheng Guo, Sho Iketani … (2022)

SARS-CoV-2 Omicron subvariants BA.2.12.1 and BA.4/5 have surged notably to become dominant in the United States and South Africa, respectively 1,2 . These new subvariants carrying further mutations in their spike proteins raise concerns that they may further evade neutralizing antibodies, thereby further compromising the efficacy of COVID-19 vaccines and therapeutic monoclonals. We now report findings from a systematic antigenic analysis of these surging Omicron subvariants. BA.2.12.1 is only modestly (1.8-fold) more resistant to sera from vaccinated and boosted individuals than BA.2. However, BA.4/5 is substantially (4.2-fold) more resistant and thus more likely to lead to vaccine breakthrough infections. Mutation at spike residue L452 found in both BA.2.12.1 and BA.4/5 facilitates escape from some antibodies directed to the so-called class 2 and 3 regions of the receptor-binding domain 3 . The F486V mutation found in BA.4/5 facilitates escape from certain class 1 and 2 antibodies but compromises the spike affinity for the viral receptor. The R493Q reversion mutation, however, restores receptor affinity and consequently the fitness of BA.4/5. Among therapeutic antibodies authorized for clinical use, only bebtelovimab retains full potency against both BA.2.12.1 and BA.4/5. The Omicron lineage of SARS-CoV-2 continues to evolve, successively yielding subvariants that are not only more transmissible but also more evasive to antibodies.

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Underlying Medical Conditions Associated with Higher Risk for Severe COVID-19: Information for Healthcare Prfessionals

(2025)

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Author and article information

Journal

Journal ID (nlm-ta): medRxiv

Journal ID (publisher-id): MEDRXIV

Title: medRxiv

Publisher: Cold Spring Harbor Laboratory

Publication date (Electronic): 06 August 2022

Electronic Location Identifier: 2022.08.04.22278450

Affiliations

[1 ]Center for Science, Health, and Society, Case Western Reserve University School of Medicine, Cleveland, OH, USA

[2 ]National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA

[3 ]Center for Community Health Integration, Case Western Reserve University School of Medicine, Cleveland, OH, USA

[4 ]The Center for Clinical Informatics Research and Education, The MetroHealth System, Cleveland, OH, USA

[5 ]Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA

Author notes

Contributors

RX conceived and designed the study and drafted the manuscript. LW performed data analysis and prepared tables and figures and participated in manuscript preparation. NDV, NAB, PBD, DCK critically contributed to study design, result interpretation and manuscript preparation. We confirm the originality of content. RX had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Corresponding Author: Rong Xu, PhD, Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, rxx@ 123456case.edu , Phone: 216-3680023

Article

DOI: 10.1101/2022.08.04.22278450

PMC ID: 9387159

PubMed ID: 35982673

SO-VID: 3d82c879-1ccb-49a2-9555-a447acd1b05a

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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