Trends, variation, and clinical characteristics of recipients of antiviral drugs and neutralising monoclonal antibodies for covid-19 in community settings: retrospective, descriptive cohort study of 23.4 million people in OpenSAFELY
Ben Goldacre,
David Evans,
Sam Harper,
Orla Macdonald,
Alex J Walker,
Richard Croker,
William J Hulme,
Colm D Andrews,
Laurie A Tomlinson,
Krishnan Bhaskaran,
Henry Drysdale,
Nicholas J DeVito,
Ian J Douglas,
Caroline E Morton,
Jessica Morley,
Bang Zheng,
Brian MacKenna,
Stephen J W Evans,
Christopher T Rentsch,
Helen J Curtis,
Amir Mehrkar,
Peter Inglesby,
Jonathan Cockburn,
John Parry,
Frank Hester,
Rose Higgins,
Simon Davy,
John Tazare,
Viyaasan Mahalingasivam,
George Hickman,
Tom Ward,
Rebecca M Smith,
Amelia C A Green,
Louis Fisher,
Sebastian C J Bacon,
Robin Y Park,
Jon Massey,
Iain Dillingham,
Linda Nab,
Christopher Bates,
Lisa E M Hopcroft,
Milan Wiedemann
Affiliations
Ben Goldacre
11 Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
David Evans
The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Sam Harper
TPP, Leeds, UK
Orla Macdonald
Oxford Health NHS Foundation Trust, Oxford, UK
Alex J Walker
The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Richard Croker
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
William J Hulme
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Colm D Andrews
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Laurie A Tomlinson
1 London School of Hygiene & Tropical Medicine, London, UK
Krishnan Bhaskaran
2 London School of Hygiene and Tropical Medicine, London, UK
Henry Drysdale
1 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Nicholas J DeVito
Nuffield Primary Care Health Sciences, University of Oxford, Oxford, UK
Ian J Douglas
professor
Caroline E Morton
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Jessica Morley
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Bang Zheng
1 London School of Hygiene & Tropical Medicine, London, UK
Brian MacKenna
10 NHS England, Redditch, UK
Stephen J W Evans
London School of Hygiene and Tropical Medicine, London, UK
Christopher T Rentsch
Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
Helen J Curtis
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Amir Mehrkar
11 Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Peter Inglesby
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Jonathan Cockburn
TPP, Leeds, UK
John Parry
TPP, Leeds, UK
Frank Hester
TPP, Leeds, UK
Rose Higgins
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Simon Davy
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
John Tazare
1 London School of Hygiene & Tropical Medicine, London, UK
Viyaasan Mahalingasivam
1 London School of Hygiene & Tropical Medicine, London, UK
George Hickman
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Tom Ward
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Rebecca M Smith
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Amelia C A Green
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Louis Fisher
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Sebastian C J Bacon
1 Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Unviersity of Oxford, Oxford, UK
Robin Y Park
1 Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Unviersity of Oxford, Oxford, UK
Jon Massey
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Iain Dillingham
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Linda Nab
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Christopher Bates
6 TPP, Leeds, UK
Lisa E M Hopcroft
Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Milan Wiedemann
Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
Objective To ascertain patient eligibility status and describe coverage of antiviral drugs and neutralising monoclonal antibodies (nMAB) as treatment for covid-19 in community settings in England.Design Retrospective, descriptive cohort study, approved by NHS England.Setting Routine clinical data from 23.4 million people linked to data on covid-19 infection and treatment, within the OpenSAFELY-TPP database.Participants Outpatients with covid-19 at high risk of severe outcomes.Interventions Nirmatrelvir/ritonavir (paxlovid), sotrovimab, molnupiravir, casirivimab/imdevimab, or remdesivir, used in the community by covid-19 medicine delivery units.Results 93 870 outpatients with covid-19 were identified between 11 December 2021 and 28 April 2022 to be at high risk of severe outcomes and therefore potentially eligible for antiviral or nMAB treatment (or both). Of these patients, 19 040 (20%) received treatment (sotrovimab, 9660 (51%); molnupiravir, 4620 (24%); paxlovid, 4680 (25%); casirivimab/imdevimab, 50 (<1%); and remdesivir, 30 (<1%)). The proportion of patients treated increased from 9% (190/2220) in the first week of treatment availability to 29% (460/1600) in the latest week. The proportion treated varied by high risk group, being lowest in those with liver disease (16%; 95% confidence interval 15% to 17%); by treatment type, with sotrovimab favoured over molnupiravir and paxlovid in all but three high risk groups (Down's syndrome (35%; 30% to 39%), rare neurological conditions (45%; 43% to 47%), and immune deficiencies (48%; 47% to 50%)); by age, ranging from ≥80 years (13%; 12% to 14%) to 50-59 years (23%; 22% to 23%); by ethnic group, ranging from black (11%; 10% to 12%) to white (21%; 21% to 21%); by NHS region, ranging from 13% (12% to 14%) in Yorkshire and the Humber to 25% (24% to 25%) in the East of England); and by deprivation level, ranging from 15% (14% to 15%) in the most deprived areas to 23% (23% to 24%) in the least deprived areas. Groups that also had lower coverage included unvaccinated patients (7%; 6% to 9%), those with dementia (6%; 5% to 7%), and care home residents (6%; 6% to 7%).Conclusions Using the OpenSAFELY platform, we were able to identify patients with covid-19 at high risk of severe outcomes who were potentially eligible to receive treatment and assess the coverage of these new treatments among these patients. In the context of a rapid deployment of a new service, the NHS analytical code used to determine eligibility could have been over-inclusive and some of the eligibility criteria not fully captured in healthcare data. However targeted activity might be needed to resolve apparent lower treatment coverage observed among certain groups, in particular (at present): different NHS regions, ethnic groups, people aged ≥80 years, those living in socioeconomically deprived areas, and care home residents.
