Evidence map›Paper›PMID 39320890›Full record

ArticleJAMA network open2024

Emerging SARS-CoV-2 Resistance After Antiviral Treatment.

Trevor J Tamura, Manish C Choudhary, Rinki Deo, Fizah Yousuf, Anadela Navarrete Gomez, Gregory E Edelstein, Julie Boucau, Owen T Glover, Mamadou Barry, Rebecca F Gilbert and 18 more

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Trial
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  11. Potency ofThe Kobe journal of medical sciences · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Protracted SARS-CoV-2 Infection in B-cell Depleted Patients: Immunologic and Viral Characteristics and Response to Dual and Extended Antiviral Therapy.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
  16. A bireporter recombinant SARS-CoV-2 Omicron BA.5 forbioRxiv : the preprint server for biology · 2026
    Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

28 authors.

Trevor J TamuraBrigham and Women's Hospital, Boston, Massachusetts.
Manish C ChoudharyBrigham and Women's Hospital, Boston, Massachusetts.
Rinki DeoBrigham and Women's Hospital, Boston, Massachusetts.
Fizah YousufBrigham and Women's Hospital, Boston, Massachusetts.
Anadela Navarrete GomezBrigham and Women's Hospital, Boston, Massachusetts.
Gregory E EdelsteinBrigham and Women's Hospital, Boston, Massachusetts.
Julie BoucauRagon Institute of Massachusetts General Hospital, MIT and Harvard, Cambridge.
Owen T GloverRagon Institute of Massachusetts General Hospital, MIT and Harvard, Cambridge.
Mamadou BarryMassachusetts General Hospital, Boston.
Rebecca F GilbertMassachusetts General Hospital, Boston.
Zahra ReynoldsMassachusetts General Hospital, Boston.
Yijia LiBrigham and Women's Hospital, Boston, Massachusetts.
Dessie TienMassachusetts General Hospital, Boston.
Tammy D VyasMassachusetts General Hospital, Boston.
Eliza PassellMassachusetts General Hospital, Boston.
Karry SuMassachusetts General Hospital, Boston.
Sarah DrapkinMassachusetts General Hospital, Boston.
Emory G AbarMassachusetts General Hospital, Boston.
Yumeko KawanoBrigham and Women's Hospital, Boston, Massachusetts.
Jeffrey A SparksBrigham and Women's Hospital, Boston, Massachusetts.
Zachary S WallaceHarvard Medical School, Boston, Massachusetts.
Jatin M VyasBrigham and Women's Hospital, Boston, Massachusetts.
Robert W ShaferStanford University School of Medicine, Palo Alto, California.
Mark J SiednerHarvard Medical School, Boston, Massachusetts.
Amy K BarczakHarvard Medical School, Boston, Massachusetts.
Jacob E LemieuxHarvard Medical School, Boston, Massachusetts.
Jonathan Z LiBrigham and Women's Hospital, Boston, Massachusetts.
POSITIVES Study Team

Funding

The impact of HIV viral diversity and cellular immunity on HIV pathogenesisP30AI060354 · NIAID · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI ARTHUR Y KIM · 2004 to 2026
$94.4M
Viral Genomics: evolution, spread, and host interactionsU19AI110818 · NIAID · BROAD INSTITUTE, INC. · PI NEAFSEY, DANIEL E · 2014 to 2024
$66.5M
HIV Drug Resistance DatabaseR24AI136618 · NIAID · STANFORD UNIVERSITY · PI ROBERT William SHAFER · 2018 to 2026
$7.3M
Characterization of Persistent COVID-19R01AI176287 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI Amy K Barczak, Jonathan Li · 2023 to 2026
$3.4M
NIAID NIH HHS P30 AI060354NIAID NIH HHS R01 AI176287NIAID NIH HHS R24 AI136618NIAID NIH HHS U19 AI110818
6 · The paper itself

Abstract

Importance: Previous studies have identified mutations in SARS-CoV-2 strains that confer resistance to nirmatrelvir, yet how often this resistance arises and its association with posttreatment virologic rebound is not well understood. Objective: To examine the prevalence of emergent antiviral resistance after nirmatrelvir treatment and its association with virologic rebound. Design, Setting, and Participants: This cohort study enrolled outpatient adults with acute COVID-19 infection from May 2021 to October 2023. Participants were divided into those who received antiviral therapy and those who did not. The study was conducted at a multicenter health care system in Boston, Massachusetts. Exposure: Treatment regimen, including none, nirmatrelvir, and remdesivir. Main Outcomes and Measures: The primary outcome was emergent SARS-CoV-2 antiviral resistance, defined as the detection of antiviral resistance mutations, which were not present at baseline, were previously associated with decreased antiviral efficacy, and emerged during or after completion of a participant's treatment. Next-generation sequencing was used to detect low frequency mutations down to 1% of the total viral population. Results: Overall, 156 participants (114 female [73.1%]; median [IQR] age, 56 [38-69] years) were included. Compared with 63 untreated individuals, the 79 who received nirmatrelvir were older and more commonly immunosuppressed. After sequencing viral RNA from participants' anterior nasal swabs, nirmatrelvir resistance mutations were detected in 9 individuals who received nirmatrelvir (11.4%) compared with 2 of those who did not (3.2%) (P = .09). Among the individuals treated with nirmatrelvir, those who were immunosuppressed had the highest frequency of resistance emergence (5 of 22 [22.7%]), significantly greater than untreated individuals (2 of 63 [3.1%]) (P = .01). Similar rates of nirmatrelvir resistance were found in those who had virologic rebound (3 of 23 [13.0%]) vs those who did not (6 of 56 [10.7%]) (P = .86). Most of these mutations (10 of 11 [90.9%]) were detected at low frequencies (<20% of viral population) and reverted to the wild type at subsequent time points. Emerging remdesivir resistance mutations were only detected in immunosuppressed individuals (2 of 14 [14.3%]) but were similarly low frequency and transient. Global Initiative on Sharing All Influenza Data analysis showed no evidence of increased nirmatrelvir resistance in the United States after the authorization of nirmatrelvir. Conclusions and Relevance: In this cohort study of 156 participants, treatment-emergent nirmatrelvir resistance mutations were commonly detected, especially in individuals who were immunosuppressed. However, these mutations were generally present at low frequencies and were transient in nature, suggesting a low risk for the spread of nirmatrelvir resistance in the community with the current variants and drug usage patterns.

Indexed as

Adenosine MonophosphateAlanineAntiviral AgentsCOVID-19 Drug TreatmentDrug Resistance, ViralSARS-CoV-2AdultAgedCohort StudiesCOVID-19FemaleHumansMaleMiddle AgedMutationAdenosine MonophosphateAlanineAntiviral Agentsremdesivir

Identifiers

PMID39320890
PMCPMC11425144

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.