Comparative effectiveness of sotrovimab and molnupiravir for preventing severe COVID-19 outcomes in patients on kidney replacement therapy: observational study using the OpenSAFELY-UKRR and SRR databases.

COVID-19 cohort studies comparative effectiveness research renal replacement therapy

Journal

Clinical kidney journal
ISSN: 2048-8505
Titre abrégé: Clin Kidney J
Pays: England
ID NLM: 101579321

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 27 04 2023
medline: 2 11 2023
pubmed: 2 11 2023
entrez: 2 11 2023
Statut: epublish

Résumé

Due to limited inclusion of patients on kidney replacement therapy (KRT) in clinical trials, the effectiveness of coronavirus disease 2019 (COVID-19) therapies in this population remains unclear. We sought to address this by comparing the effectiveness of sotrovimab against molnupiravir, two commonly used treatments for non-hospitalised KRT patients with COVID-19 in the UK. With the approval of National Health Service England, we used routine clinical data from 24 million patients in England within the OpenSAFELY-TPP platform linked to the UK Renal Registry (UKRR) to identify patients on KRT. A Cox proportional hazards model was used to estimate hazard ratios (HRs) of sotrovimab versus molnupiravir with regards to COVID-19-related hospitalisations or deaths in the subsequent 28 days. We also conducted a complementary analysis using data from the Scottish Renal Registry (SRR). Among the 2367 kidney patients treated with sotrovimab ( In routine care of non-hospitalised patients with COVID-19 on KRT, sotrovimab was associated with a lower risk of severe COVID-19 outcomes compared with molnupiravir during Omicron waves.

Sections du résumé

Background UNASSIGNED
Due to limited inclusion of patients on kidney replacement therapy (KRT) in clinical trials, the effectiveness of coronavirus disease 2019 (COVID-19) therapies in this population remains unclear. We sought to address this by comparing the effectiveness of sotrovimab against molnupiravir, two commonly used treatments for non-hospitalised KRT patients with COVID-19 in the UK.
Methods UNASSIGNED
With the approval of National Health Service England, we used routine clinical data from 24 million patients in England within the OpenSAFELY-TPP platform linked to the UK Renal Registry (UKRR) to identify patients on KRT. A Cox proportional hazards model was used to estimate hazard ratios (HRs) of sotrovimab versus molnupiravir with regards to COVID-19-related hospitalisations or deaths in the subsequent 28 days. We also conducted a complementary analysis using data from the Scottish Renal Registry (SRR).
Results UNASSIGNED
Among the 2367 kidney patients treated with sotrovimab (
Conclusions UNASSIGNED
In routine care of non-hospitalised patients with COVID-19 on KRT, sotrovimab was associated with a lower risk of severe COVID-19 outcomes compared with molnupiravir during Omicron waves.

Identifiants

pubmed: 37915915
doi: 10.1093/ckj/sfad184
pii: sfad184
pmc: PMC10616487
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2048-2058

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.

Déclaration de conflit d'intérêts

B.G. has received research funding from the Laura and John Arnold Foundation, NIHR, NIHR School of Primary Care Research, NHS England, NIHR Oxford Biomedical Research Centre, Mohn–Westlake Foundation, NIHR Applied Research Collaboration Oxford and Thames Valley, Wellcome Trust, Good Thinking Foundation, Health Data Research UK, Health Foundation, World Health Organization, UKRI MRC, Asthma UK, British Lung Foundation and the Longitudinal Health and Wellbeing strand of the National Core Studies programme; he is a non-executive director at NHS Digital; he also receives personal income from speaking and writing for lay audiences on the misuse of science. B.M.K. is employed by NHS England, working on medicines policy and a clinical lead for primary care medicines data. A.M. is a member of RCGP health informatics group and the NHS Digital GP data Professional Advisory Group, and received consulting fee from Induction Healthcare. E.P. was a consultant for WHO SAGE COVID-19 Vaccines Working Group. I.J.D. has received research grants from GSK and AstraZeneca and holds shares in GSK. J.T. was funded by an unrestricted grant from GSK for methodological research unrelated to this work. S.L. received remuneration for medical writing from Kidney Care UK, UK Kidney Association and GORE; support for attending meeting from UK Kidney Association; and is Chair of Patients Council of UK Kidney Association, and Secretary and Trustee of Guy's & St Thomas' Kidney Patients' Association. V.M. received grant from National Institute for Health and Care Research. E.C. is a member of UK Kidney Association Infection Prevention & Control committee. F.L. received grants to institution from AstraZeneca, Pfizer, Novartis, and payment to institution from AstraZeneca for scientific events. S.B. received consulting fees from GSK and AstraZeneca. D.N. received grants from National Institute for Health and Care Research, MRC and GSK Open Lab, unrelated to this work; and is the UKKA Director of Informatics Research. L.A.T. has received research funding from MRC, Wellcome, NIHR and GSK, consulted for Bayer in relation to an observational study of chronic kidney disease (unpaid), and is a member of 4 non-industry funded (NIHR/MRC) trial advisory committees (unpaid) and MHRA Expert advisory group (Women's Health). The other authors declare no conflicts of interest.

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Auteurs

Bang Zheng (B)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Jacqueline Campbell (J)

Scottish Renal Registry, Scottish Health Audits, Public Health Scotland, Glasgow, UK.

Edward J Carr (EJ)

Francis Crick Institute, London, UK.

John Tazare (J)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Linda Nab (L)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Viyaasan Mahalingasivam (V)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Amir Mehrkar (A)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Shalini Santhakumaran (S)

UK Renal Registry, Bristol, UK.

Retha Steenkamp (R)

UK Renal Registry, Bristol, UK.

Fiona Loud (F)

Kidney Care UK, Alton, UK.

Susan Lyon (S)

Patient Council, UK Kidney Association, Bristol, UK.

Miranda Scanlon (M)

Kidney Research UK, Peterborough, UK.

William J Hulme (WJ)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Amelia C A Green (ACA)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Helen J Curtis (HJ)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Louis Fisher (L)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Edward Parker (E)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Ben Goldacre (B)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Ian Douglas (I)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Stephen Evans (S)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Brian MacKenna (B)

Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Samira Bell (S)

Scottish Renal Registry, Scottish Health Audits, Public Health Scotland, Glasgow, UK.
Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK.

Laurie A Tomlinson (LA)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.

Dorothea Nitsch (D)

London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
UK Renal Registry, Bristol, UK.

Classifications MeSH