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Common protocol for validation of the QCOVID algorithm across the four UK nations

Kerr, Steven; Robertson, Chris; Nafilyan, Vahe; Lyons, Ronan A; Kee, Frank; Cardwell, Christopher R.; Coupland, Carol; Lyons, Jane; Humberstone, Ben; Hippisley-Cox, Julia; Sheikh, Aziz

Common protocol for validation of the QCOVID algorithm across the four UK nations Thumbnail


Authors

Steven Kerr

Chris Robertson

Vahe Nafilyan

Ronan A Lyons

Frank Kee

Christopher R. Cardwell

CAROL COUPLAND carol.coupland@nottingham.ac.uk
Professor of Medical Statistics

Jane Lyons

Ben Humberstone

Julia Hippisley-Cox

Aziz Sheikh



Abstract

Introduction The QCOVID algorithm is a risk prediction tool for infection and subsequent hospitalisation/death due to SARS-CoV-2. At the time of writing, it is being used in important policy-making decisions by the UK and devolved governments for combatting the COVID-19 pandemic, including deliberations on shielding and vaccine prioritisation. There are four statistical validations exercises currently planned for the QCOVID algorithm, using data pertaining to England, Northern Ireland, Scotland and Wales, respectively. This paper presents a common procedure for conducting and reporting on validation exercises for the QCOVID algorithm. Methods and analysis We will use open, retrospective cohort studies to assess the performance of the QCOVID risk prediction tool in each of the four UK nations. Linked datasets comprising of primary and secondary care records, virological testing data and death registrations will be assembled in trusted research environments in England, Scotland, Northern Ireland and Wales. We will seek to have population level coverage as far as possible within each nation. The following performance metrics will be calculated by strata: Harrell's C, Brier Score, R 2 and Royston's D. Ethics and dissemination Approvals have been obtained from relevant ethics bodies in each UK nation. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journal.

Journal Article Type Article
Acceptance Date May 31, 2022
Online Publication Date Jun 14, 2022
Publication Date 2022-06
Deposit Date Jul 14, 2022
Publicly Available Date Jul 14, 2022
Journal BMJ Open
Electronic ISSN 2044-6055
Publisher BMJ
Peer Reviewed Peer Reviewed
Volume 12
Issue 6
Article Number e050994
DOI https://doi.org/10.1136/bmjopen-2021-050994
Keywords General Medicine
Public URL https://nottingham-repository.worktribe.com/output/8952432
Publisher URL https://bmjopen.bmj.com/content/12/6/e050994