Article Text

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 Wong1,
  2. Brian MacKenna2,
  3. Caroline E Morton2,
  4. Anna Schultze1,
  5. Alex J Walker2,
  6. Krishnan Bhaskaran1,
  7. Jeremy P Brown1,
  8. Christopher T Rentsch1,
  9. Elizabeth Williamson1,
  10. Henry Drysdale2,
  11. Richard Croker2,
  12. Seb Bacon2,
  13. William Hulme2,
  14. Chris Bates3,
  15. Helen J Curtis2,
  16. Amir Mehrkar2,
  17. David Evans2,
  18. Peter Inglesby2,
  19. Jonathan Cockburn3,
  20. Helen I McDonald1,
  21. Laurie Tomlinson1,
  22. Rohini Mathur1,
  23. Kevin Wing1,
  24. Harriet Forbes1,
  25. Rosalind M Eggo1,
  26. John Parry3,
  27. Frank Hester3,
  28. Sam Harper3,
  29. Stephen JW Evans1,
  30. Liam Smeeth1,
  31. Ian J Douglas1,
  32. Ben Goldacre2
  33. The OpenSAFELY Collaborative
  1. 1 Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
  2. 2 The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, Oxfordshire, UK
  3. 3 TPP, Leeds, UK
  1. Correspondence to Dr Angel YS Wong, London School of Hygiene & Tropical Medicine, London, UK; angel.wong{at}lshtm.ac.uk

Abstract

Objectives To assess the association between routinely prescribed non-steroidal anti-inflammatory drugs (NSAIDs) and deaths from COVID-19 using OpenSAFELY, a secure analytical platform.

Methods We conducted two cohort studies from 1 March to 14 June 2020. Working on behalf of National Health Service England, we used routine clinical data in England linked to death data. In study 1, we identified people with an NSAID prescription in the last 3 years from the general population. In study 2, we identified people with rheumatoid arthritis/osteoarthritis. We defined exposure as current NSAID prescription within the 4 months before 1 March 2020. We used Cox regression to estimate HRs for COVID-19 related death in people currently prescribed NSAIDs, compared with those not currently prescribed NSAIDs, accounting for age, sex, comorbidities, other medications and geographical region.

Results In study 1, we included 536 423 current NSAID users and 1 927 284 non-users in the general population. We observed no evidence of difference in risk of COVID-19 related death associated with current use (HR 0.96, 95% CI 0.80 to 1.14) in the multivariable-adjusted model. In study 2, we included 1 708 781 people with rheumatoid arthritis/osteoarthritis, of whom 175 495 (10%) were current NSAID users. In the multivariable-adjusted model, we observed a lower risk of COVID-19 related death (HR 0.78, 95% CI 0.64 to 0.94) associated with current use of NSAID versus non-use.

Conclusions We found no evidence of a harmful effect of routinely prescribed NSAIDs on COVID-19 related deaths. Risks of COVID-19 do not need to influence decisions about the routine therapeutic use of NSAIDs.

  • arthritis
  • rheumatoid
  • COVID-19
  • epidemiology
  • osteoarthritis

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. All code for data management and analyses in addition to the prespecified protocol are archived at: https://github.com/opensafely/nsaids-covid-research. All codelists for identifying exposures, covariates and outcomes are openly shared at https://codelists.opensafely.org/. Access to the platform is via a virtual private network connection, restricted to a small group of researchers. All data relevant to the study are included in the article or uploaded as supplementary information

https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

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Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. All code for data management and analyses in addition to the prespecified protocol are archived at: https://github.com/opensafely/nsaids-covid-research. All codelists for identifying exposures, covariates and outcomes are openly shared at https://codelists.opensafely.org/. Access to the platform is via a virtual private network connection, restricted to a small group of researchers. All data relevant to the study are included in the article or uploaded as supplementary information

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Footnotes

  • Handling editor Josef S Smolen

  • AYW, BM and CEM contributed equally.

  • Contributors BG is the guarantor. LS, BG and ID contributed to conceptualisation of the study. CB, JP, JC, SH, SB, DE, PI and CM contributed to data curation. AYSW, BM, CM and JB did the formal analysis. BG and LS acquired funding for the study. AM, BG, CB and JP were responsible for work relating to information governance. ID, AYSW, AS, LT, KW, KB, CR, EW, SE, LS, JB, CM, AJW, BM, SB and BG contributed to the study methods. BM, CM, AJW, RC, AS, CR, PI, SB, DE, CB, JC, JP, SH, HD, HC, KB, SB, AM, LT, ID, HM, RM, HF and RE contributed to disease category conceptualisation and codelists. HC, EW, LS and BG acquired ethics approval for this study. AYSW, BM, CM, AS, AJW, CR, WH, CB, SB, AM, LS and BG contributed to project administration. BG and LS acquired resources. SB, DE, PI, AJW, CM, CB, FH, JC and SH created and maintained software. ID, LS and BG supervised the study. AYSW, JB and KB did the visualisation. AYSW, BM, CM, ID and JB wrote the original manuscript draft. All authors contributed to reviewing and editing of the manuscript. All authors were involved in design and conceptual development and reviewed and approved the final manuscript. ID and BG are joint principal investigators.

  • Funding TPP provided technical expertise and infrastructure within their data centre pro bono in the context of a national emergency. BG’s work on better use of data in healthcare more broadly is currently funded in part by: National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, the Mohn-Westlake Foundation, NHS England and the Health Foundation; all DataLab staff are supported by BG’s grants on this work. LS reports grants from Wellcome, MRC, NIHR, UKRI, British Council, GlaxoSmithKline, British Heart Foundation, and Diabetes UK outside this work. AYSW holds a fellowship from British Heart Foundation. JPB is funded by a studentship from GlaxoSmithKline. AS is employed by London School of Hygiene and Tropical Medicine on a fellowship sponsored by GlaxoSmithKline. KB holds a Sir Henry Dale fellowship jointly funded by Wellcome and the Royal Society (107731/Z/15/Z)). HIM is funded by the National Institute for Health Research (NIHR) Health Protection Research Unit in Immunisation, a partnership between Public Health England and London School of Hygiene and Tropical Medicine. RM holds a Sir Henry Wellcome fellowship (201375/Z/16/Z)). EW holds grants from MRC. RG holds grants from NIHR and MRC. ID holds grants from NIHR and GlaxoSmithKline. HF holds a UKRI fellowship.

  • Disclaimer The views expressed are those of the authors and not necessarily those of the NIHR, NHS England, Public Health England or the Department of Health and Social Care.

  • Competing interests BG has received research funding from Health Data Research UK, the Laura and John Arnold Foundation, the Wellcome Trust, the NIHR Oxford Biomedical Research Centre, the NHS National Institute for Health Research School of Primary Care Research, the Mohn-Westlake Foundation, the Good Thinking Foundation, the Health Foundation and the World Health Organisation; he also receives personal income from speaking and writing for lay audiences on the misuse of science. ID has received unrestricted research grants and holds shares in GlaxoSmithKline.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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