Predicting COVID-19 related death using the OpenSAFELY platform

medRxiv

Abstract

Abstract Objectives To compare approaches for obtaining relative and absolute estimates of risk of 28-day COVID-19 mortality for adults in the general population of England in the context of changing levels of circulating infection. Design Three designs were compared. (A) case-cohort which does not explicitly account for the time-changing prevalence of COVID-19 infection, (B) 28-day landmarking, a series of sequential overlapping sub-studies incorporating time-updating proxy measures of the prevalence of infection, and (C) daily landmarking. Regression models were fitted to predict 28-day COVID-19 mortality. Setting Working on behalf of NHS England, we used clinical data from adult patients from all regions of England held in the TPP SystmOne electronic health record system, linked to Office for National Statistics (ONS) mortality data, using the OpenSAFELY platform. Participants Eligible participants were adults aged 18 or over, registered at a general practice using TPP software on 1 st March 2020 with recorded sex, postcode and ethnicity. 11,972,947 individuals were included, and 7,999 participants experienced a COVID-19 related death. The study period lasted 100 days, ending 8 th June 2020. Predictors A range of demographic characteristics and comorbidities were used as potential predictors. Local infection prevalence was estimated with three proxies: modelled based on local prevalence and other key factors; rate of A&E COVID-19 related attendances; and rate of suspected COVID-19 cases in primary care. Main outcome measures COVID-19 related death. Results All models discriminated well between patients who did and did not experience COVID-19 related death, with C-statistics ranging from 0.92-0.94. Accurate estimates of absolute risk required data on local infection prevalence, with modelled estimates providing the best performance. Conclusions Reliable estimates of absolute risk need to incorporate changing local prevalence of infection. Simple models can provide very good discrimination and may simplify implementation of risk prediction tools in practice.

Authors 43

1. Elizabeth Williamson

   London School of Hygiene & Tropical Medicine

   Affiliation as printed

   London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

2. John Tazare

   London School of Hygiene & Tropical Medicine

   Affiliation as printed

   London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

3. Krishnan Bhaskaran

   London School of Hygiene & Tropical Medicine

   Affiliation as printed

   London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

4. Helen I McDonald

   University of Oxford · London School of Hygiene & Tropical Medicine

   Affiliation as printed

   London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

   The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

5. Alex J Walker

   University of Oxford · London School of Hygiene & Tropical Medicine

   Affiliation as printed

   The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

   London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

6. Laurie A. Tomlinson

   London School of Hygiene & Tropical Medicine

   Affiliation as printed

   London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

7. Kevin Wing

   University of Oxford · London School of Hygiene & Tropical Medicine

   Affiliation as printed

   London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

   The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

8. Seb Bacon

   University of Oxford

   Affiliation as printed

   The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

   TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX

9. Chris J Bates

   University of Oxford

   Affiliation as printed

   TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX

   The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

10. Helen J Curtis

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

11. Harriet J. Forbes

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

12. Caroline Minassian

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

13. Caroline E Morton

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

14. Emily Nightingale

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

15. Amir Mehrkar

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

16. David Evans

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

17. Brian David Nicholson

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

18. Dave Leon

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

19. Peter Inglesby

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

20. Brian MacKenna

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

21. Nicholas G. M. Davies

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

22. Nicholas DeVito

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

23. Henry Drysdale

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

    TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX

24. Jonathan Cockburn

    University of Oxford

    Affiliation as printed

    TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

25. William J. Hulme

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

26. Jess Morley

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

27. Ian Douglas

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

28. Christopher T. Rentsch

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

29. Rohini Mathur

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

30. Angel Y. S. Wong

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

31. Anna Schultze

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

32. Richard Croker

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

    TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX

33. Frank Hester
    Affiliation as printed

    TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX

34. Sam B. Harper

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

35. Richard Grieve

    London School of Hygiene & Tropical Medicine · Intensive Care National Audit & Research Centre

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

    Intensive Care National Audit & Research Centre (ICNARC), 24 High Holborn, Holborn, London WC1V 6AZ

36. David A Harrison Aachen

    Leiden University Medical Center · Intensive Care National Audit & Research Centre

    Affiliation as printed

    Intensive Care National Audit & Research Centre (ICNARC), 24 High Holborn, Holborn, London WC1V 6AZ

    Leiden University Medical Center, Leiden, the Netherlands

37. Ewout Willem Steyerberg Aachen

    Leiden University Medical Center · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    Leiden University Medical Center, Leiden, the Netherlands

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

38. Rosalind M. Eggo

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

39. Karla Diaz‐Ordaz

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

40. Ruth H. Keogh

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

41. Stephen Evans

    London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

42. Liam L Smeeth corresponding

    University of Oxford · London School of Hygiene & Tropical Medicine

    Affiliation as printed

    London School of Hygiene and Tropical Medicine, Faculty of Epidemiology & Population Health, Keppel Street, London WCE 7HT

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG

43. Ben M. Goldacre corresponding

    University of Oxford

    Affiliation as printed

    The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG