Identification of drugs associated with reduced severity of COVID-19: A case-control study in a large population

  1. Ariel Israel  Is a corresponding author
  2. Alejandro A Schäffer
  3. Assi Cicurel
  4. Ilan Feldhamer
  5. Ameer Tal
  6. Kuoyuan Cheng
  7. Sanju Sinha
  8. Eyal Schiff
  9. Gil Lavie
  10. Eytan Ruppin  Is a corresponding author
  1. Clalit Health Services, Israel
  2. National Institutes of Health, United States
  3. Sheba Medical Center, Israel
  4. Tel-Aviv University, Israel

Abstract

Background: Until COVID-19 drugs specifically developed to treat COVID-19 become more widely accessible, it is crucial to identify whether existing medications have a protective effect against severe disease. Towards this objective, we conducted a large population study in Clalit Health Services (CHS), the largest healthcare provider in Israel, insuring over 4.7 million members.

Methods: Two case-control matched cohorts were assembled to assess which medications, acquired in the last month, decreased the risk of COVID‑19 hospitalization. Case patients were adults aged 18-95 hospitalized for COVID-19. In the first cohort, five control patients, from the general population, were matched to each case (n=6202); in the second cohort, two non-hospitalized SARS-CoV-2 positive control patients were matched to each case (n=6919). The outcome measures for a medication were: odds ratio (OR) for hospitalization, 95% confidence interval (CI), and the p‑value, using Fisher's exact test. False discovery rate was used to adjust for multiple testing.

Results: Medications associated with most significantly reduced odds for COVID-19 hospitalization include: ubiquinone (OR=0.185, 95% CI (0.058 to 0.458), p<0.001), ezetimibe (OR=0.488, 95% CI ((0.377 to 0.622)), p<0.001), rosuvastatin (OR=0.673, 95% CI (0.596 to 0.758), p<0.001), flecainide (OR=0.301, 95% CI (0.118 to 0.641), p<0.001), and vitamin D (OR=0.869, 95% CI (0.792 to 0.954), p<0.003). Remarkably, acquisition of artificial tears, eye care wipes, and several ophthalmological products were also associated with decreased risk for hospitalization.

Conclusions: Ubiquinone, ezetimibe and rosuvastatin, all related to the cholesterol synthesis pathway were associated with reduced hospitalization risk. These findings point to a promising protective effect which should be further investigated in controlled, prospective studies.

Funding: This research was supported in part by the Intramural Research Program of the National Institutes of Health, NCI.

Data availability

Data were obtained from patients' electronic health records, and IRB approval restrains its use to researchers inside Clalit Health Services. For further information regarding data availability, researchers may contact Dr. Lavie gillav@clalit.org.ilThis study is based on real-world patient drug purchases, and it cannot be made available due to patient privacy concerns. R code used to produce Figure 1 is available as Supplemental File 1.

Article and author information

Author details

  1. Ariel Israel

    Department of Research and Data, Clalit Health Services, Tel-Aviv, Israel
    For correspondence
    dr.ariel.israel@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4389-8896
  2. Alejandro A Schäffer

    Cancer Data Science Laboratory, , National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Assi Cicurel

    Department of Research and Data, Division of Planning and Strategy, Clalit Health Services, Tel-Aviv, Israel
    Competing interests
    The authors declare that no competing interests exist.
  4. Ilan Feldhamer

    Department of Research and Data, Clalit Health Services, Tel-Aviv, Israel
    Competing interests
    The authors declare that no competing interests exist.
  5. Ameer Tal

    Department of Research and Data, Clalit Health Services, Tel-Aviv, Israel
    Competing interests
    The authors declare that no competing interests exist.
  6. Kuoyuan Cheng

    Cancer Data Science Laboratory, , National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Sanju Sinha

    Cancer Data Science Laboratory, , National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Eyal Schiff

    Tel-Aviv University, Sheba Medical Center, Ramat Gan, Israel
    Competing interests
    The authors declare that no competing interests exist.
  9. Gil Lavie

    Department of Research and Data, Division of Planning and Strategy, Clalit Health Services, Tel-Aviv, Israel
    Competing interests
    The authors declare that no competing interests exist.
  10. Eytan Ruppin

    Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
    For correspondence
    eytan.ruppin@nih.gov
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Cancer Institute (Intramural funding)

  • Alejandro A Schäffer
  • Kuoyuan Cheng
  • Sanju Sinha
  • Eytan Ruppin

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: This study has been approved by the CHS Institutional Review Board (IRB) with a waiver of informed consent, approval number: COM-0046-20.

Reviewing Editor

  1. Frank L van de Veerdonk, Radboudumc Center for Infectious Diseases, Netherlands

Publication history

  1. Preprint posted: October 14, 2020 (view preprint)
  2. Received: March 7, 2021
  3. Accepted: July 7, 2021
  4. Accepted Manuscript published: July 27, 2021 (version 1)
  5. Version of Record published: July 29, 2021 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Ariel Israel
  2. Alejandro A Schäffer
  3. Assi Cicurel
  4. Ilan Feldhamer
  5. Ameer Tal
  6. Kuoyuan Cheng
  7. Sanju Sinha
  8. Eyal Schiff
  9. Gil Lavie
  10. Eytan Ruppin
(2021)
Identification of drugs associated with reduced severity of COVID-19: A case-control study in a large population
eLife 10:e68165.
https://doi.org/10.7554/eLife.68165
  1. Further reading

Further reading

    1. Medicine
    2. Microbiology and Infectious Disease
    3. Epidemiology and Global Health
    4. Immunology and Inflammation
    Edited by Jos WM van der Meer et al.
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    1. Epidemiology and Global Health
    Nikkil Sudharsanan et al.
    Research Article

    Background:

    Fear over side-effects is one of the main drivers of COVID-19 vaccine hesitancy. A large literature in the behavioral and communication sciences finds that how risks are framed and presented to individuals affects their judgments of its severity. However, it remains unknown whether such framing changes can affect COVID-19 vaccine behavior and be deployed as policy solutions to reduce hesitancy.

    Methods:

    We conducted a pre-registered randomized controlled trial among 8998 participants in the United States and the United Kingdom to examine the effects of different ways of framing and presenting vaccine side-effects on individuals’ willingness to get vaccinated and their perceptions of vaccine safety.

    Results:

    Adding a descriptive risk label (‘very low risk’) next to the numerical side-effect and providing a comparison to motor-vehicle mortality increased participants’ willingness to take the COVID-19 vaccine by 3.0 percentage points (p=0.003) and 2.4 percentage points (p=0.049), respectively. These effects were independent and additive and combining both framing strategies increased willingness to receive the vaccine by 6.1 percentage points (p<0.001). Mechanistically, we find evidence that these framing effects operate by increasing individuals’ perceptions of how safe the vaccine is.

    Conclusions:

    Low-cost side-effect framing strategies can meaningfully affect vaccine intentions at a population level.

    Funding:

    Heidelberg Institute of Global Health.

    Clinical trial number:

    German Clinical Trials Registry (#DRKS00025551).