Dupilumab Use Is Associated With Protection From Coronavirus Disease 2019 Mortality: A Retrospective Analysis

  1. Alexandra N Donlan
  2. Indika Mallawaarachchi
  3. Jennifer M Sasson
  4. Robert Preissner
  5. Johanna J Loomba
  6. William A Petri

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

We previously found that type 2 immunity promotes coronavirus disease 2019 (COVID-19) pathogenesis in a mouse model. To test relevance to human disease, we used electronic health record databases and determined that patients on dupilumab (anti-interleukin [IL]-4R monoclonal antibody that blocks IL-13 and IL-4 signaling) at the time of COVID-19 infection had lower mortality.

Article activity feed

  1. Version published to 10.1093/cid/ciac745
  2. ScreenIT

    SciScore for 10.1101/2022.03.30.22273174: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Drug use was identified via RxNorm codes for dupilumab (1876376) and the lab value for C-reactive protein (9063). 1:1 matching was performed for age and sex.
    RxNorm
    suggested: (RxNorm, RRID:SCR_006645)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, there are limitations due to non-randomized groups resulting in sampling biases, difficulty defining temporal boundaries, and not being able to infer causational relationships. The N3C database used allowed for well-defined patient outcomes and temporal windows, however small sampling size may limit the statistical power through this method. Supportive analysis by TriNetX allowed for larger cohort of dupilumab (+) cases, but was limited to lower matching criteria and at a 1:1 ratio. Utilization of both datasets, then, provides two analyses which supported our hypothesis. Identification of dupilumab as a being associated with reduction in death due to COVID-19 may implicate this drug as a potential therapeutic option for patients. Future, large-scale clinical trial of dupilumab use during COVID-19 will be important for understanding the impact this drug may have on protecting patients from severe outcomes. Author contributions: AD wrote the manuscript. AD, IM, JL, and RB assisted with data analysis. All authors contributed to discussion regarding conceptualization and design of the reported studies. Authorship was determined using ICMJE recommendations. Attribution: This research was possible because of the patients whose information is included within the data and the organizations and scientists who have contributed to the on-going development of this community resource https://doi.org/10.1093/jamia/ocaa196.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2022.03.30.22273174v1 on medRxiv