Use of non-steroidal anti-inflammatory drugs and risk of death from COVID-19: an OpenSAFELY cohort analysis based on two cohorts

  1. Angel YS Wong
  2. Brian MacKenna
  3. Caroline E Morton
  4. Anna Schultze
  5. Alex J Walker
  6. Krishnan Bhaskaran
  7. Jeremy P Brown
  8. Christopher T Rentsch
  9. Elizabeth Williamson
  10. Henry Drysdale
  11. Richard Croker
  12. Seb Bacon
  13. William Hulme
  14. Chris Bates
  15. Helen J Curtis
  16. Amir Mehrkar
  17. David Evans
  18. Peter Inglesby
  19. Jonathan Cockburn
  20. Helen I McDonald
  21. Laurie Tomlinson
  22. Rohini Mathur
  23. Kevin Wing
  24. Harriet Forbes
  25. Rosalind M Eggo
  26. John Parry
  27. Frank Hester
  28. Sam Harper
  29. Stephen JW Evans
  30. Liam Smeeth
  31. Ian J Douglas
  32. Ben Goldacre

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Abstract

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  1. Version published to 10.1136/annrheumdis-2020-219517
  2. ScreenIT

    SciScore for 10.1101/2020.08.12.20171405: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Software and Reproducibility: Data management was performed using Python 3.8 and SQL, with analysis carried out using Stata 16.1.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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:
    Strengths and weaknesses: The greatest strength of this study was the power we had to examine the association between NSAIDs and COVID-19 death, particularly on types of NSAID as our dataset included medical records from almost 24 million individuals. Our study is further strengthened by the use of two different study populations for comparisons to understand the impact of confounding by indication. The breadth of data available in primary care also allows us to account for a wide range of potential confounders. Additionally, we pre-specified our analysis plan and have openly shared all analytical code. We also recognize possible limitations. First, we do not know whether patients truly took the medications as prescribed. Second, the supply of NSAIDs “over the counter” without a prescription is not captured in GP systems underpinning OpenSAFELY. However, “over the counter” purchases are likely to be for ibuprofen alone, used for acute, irregular conditions such as minor pain or fever, which might affect the results in Study 1 because people prescribed NSAIDs for different indications. However, this is unlikely to impact the result in the RA/OA population as GPs in England are still required to prescribe NSAIDS for long-term conditions such as RA/OA.44 A further limitation is that we do not capture all additional medicines commonly used in the treatment of RA. In England, a small number of medicines for long term conditions are supplied routinely by hospitals directly to patie...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT0432563340Trial number did not resolve on clinicaltrials.gov. Is the number correct?NA
    NCT0438276841Trial number did not resolve on clinicaltrials.gov. Is the number correct?NA
    NCT0433462942Trial number did not resolve on clinicaltrials.gov. Is the number correct?NA
    NCT0434445743Trial number did not resolve on clinicaltrials.gov. Is the number correct?NA

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2020.08.12.20171405v1 on medRxiv