Trends, variation and clinical characteristics of recipients of antivirals and neutralising monoclonal antibodies for non-hospitalised COVID-19: a descriptive cohort study of 23.4 million people in OpenSAFELY

  1. The OpenSAFELY Collaborative
  2. Amelia Green
  3. Helen J Curtis
  4. Rose Higgins
  5. Rebecca Smith
  6. Amir Mehrkar
  7. Peter Inglesby
  8. Viyaasan Mahalingasivam
  9. Henry Drysdale
  10. Nicholas J DeVito
  11. Richard Croker
  12. Christopher T Rentsch
  13. Krishnan Bhaskaran
  14. Colm Andrews
  15. Seb Bacon
  16. Simon Davy
  17. Iain Dillingham
  18. David Evans
  19. Louis Fisher
  20. George Hickman
  21. Lisa Hopcroft
  22. William J Hulme
  23. Linda Nab
  24. Jon Massey
  25. Orla McDonald
  26. Jessica Morley
  27. Caroline E Morton
  28. Robin Park
  29. Alex J Walker
  30. Tom Ward
  31. Milan Wiedemann
  32. Chris Bates
  33. Jonathan Cockburn
  34. John Parry
  35. Frank Hester
  36. Sam Harper
  37. Ian J Douglas
  38. Stephen JW Evans
  39. Laurie Tomlinson
  40. Brian MacKenna
  41. Ben Goldacre

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Abstract

Objectives

Ascertain patient eligibility status and describe coverage of antivirals and neutralising monoclonal antibodies (nMAB) as treatment for COVID-19 in community settings in England.

Design

Cohort study, approved by NHS England.

Setting

Routine clinical data from 23.4m people linked to data on COVID-19 infection and treatment, within the OpenSAFELY-TPP database.

Participants

Non-hospitalised COVID-19 patients at high-risk of severe outcomes.

Interventions

Nirmatrelvir/ritonavir (Paxlovid), sotrovimab, molnupiravir, casirivimab or remdesivir, administered in the community by COVID-19 Medicine Delivery Units.

Results

We identified 102,170 non-hospitalised patients with COVID-19 between 11 th December 2021 and 28 th April 2022 at high-risk of severe outcomes and therefore potentially eligible for antiviral and/or nMAB treatment. Of these patients, 18,210 (18%) received treatment; sotrovimab, 9,340 (51%); molnupiravir, 4,500 (25%); Paxlovid, 4,290 (24%); casirivimab, 50 (<1%); and remdesivir, 20 (<1%). The proportion of patients treated increased from 8% (180/2,380) in the first week of treatment availability to 22% (420/1870) in the latest week. The proportion treated varied by high risk group, lowest in those with Liver disease (12%; 95% CI 11 to 13); by treatment type, with sotrovimab favoured over molnupiravir/Paxlovid in all but three high risk groups: Down syndrome (36%; 95% CI 31 to 40), Rare neurological conditions (46%; 95% CI 44 to 48), and Primary immune deficiencies (49%; 95% CI 48 to 51); by ethnicity, from Black (10%; 95% CI 9 to 11) to White (18%; 95% CI 18 to 19); by NHS Region, from 11% (95% CI 10 to 12) in Yorkshire and the Humber to 23% (95% CI 22 to 24) in the East of England); and by deprivation level, from 12% (95% CI 12 to 13) in the most deprived areas to 21% (95% CI 21 to 22) in the least deprived areas. There was also lower coverage among unvaccinated patients (5%; 95% CI 4 to 7), those with dementia (5%; 95% CI 4 to 6) and care home residents (6%; 95% CI 5 to 6).

Conclusions

Using the OpenSAFELY platform we were able to identify patients who were potentially eligible to receive treatment and assess the coverage of these new treatments amongst these patients. Targeted activity may be needed to address apparent lower treatment coverage observed among certain groups, in particular (at present): different NHS regions, socioeconomically deprived areas, and care homes.

What is already known about this topic

Since the emergence of COVID-19, a number of approaches to treatment have been tried and evaluated. These have mainly consisted of treatments such as dexamethasone, which were used in UK hospitals,from early on in the pandemic to prevent progression to severe disease. Until recently (December 2021), no treatments have been widely used in community settings across England.

What this study adds

Following the rollout of antiviral medicines and neutralising monoclonal antibodies (nMABs) as treatment for patients with COVID-19, we were able to identify patients who were potentially eligible to receive antivirals or nMABs and assess the coverage of these new treatments amongst these patients, in as close to real-time as the available data flows would support. While the proportion of the potentially eligible patients receiving treatment increased over time, rising from 8% (180/2,380) in the first week of the roll out to 22% (420/1870) in the last week of April 2022, there were variations in coverage between key clinical, geographic, and demographic subgroup.

How this study might affect research, practice, or policy

Targeted activity may therefore be needed to address lower treatment rates observed among certain geographic areas and key groups including ethnic minorities, people living in areas of higher deprivation, and in care homes.

Article activity feed

  1. Version published to 10.1101/2022.03.07.22272026v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2022.03.07.22272026: (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
    Data management and analysis was performed using the OpenSAFELY software libraries, Python 3 and R version 4.0.2.
    Python
    suggested: (IPython, RRID:SCR_001658)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and weaknesses: The key strengths of this study are the scale, detail and completeness of the underlying raw electronic health record data. The OpenSAFELY-TPP platform runs analyses across the full dataset of all raw, pseudonymised, single-event-level clinical events for all 23.4 million current patients at all 2,545 general practices in England using TPP software; whereas the GPES dataset available in NHS Digital is a subset of this raw data created through a series of processing rules for specific aspects of GP records applied at source before extraction. OpenSAFELY-TPP also provides data in near-real time, providing unprecedented opportunities for audit and feedback to rapidly identify and resolve concerns around health service activity and clinical outcomes related to the COVID-19 pandemic. The delay from entry of a clinical event into the EHR to its appearing in the OpenSAFELY-TPP platform varies from two to nine days. This is substantially faster than any other source of comprehensive GP data. Additionally OpenSAFELY now contains linked COVID-19 therapeutics data which is collected from CMDUs with typically only 2-3 days delay between form submission and data being available for analysis. This can support timely monitoring of treatments administered through CMDUs as well as safety and efficacy studies of these treatments and other COVID-19 analyses. We recognise some limitations to our analysis. Our population, although extremely large, may not be fully repres...

    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

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  3. Version published to 10.1101/2022.03.07.22272026v1 on medRxiv