University of Leicester
Browse
An international comparison of Presentation Outcomes and CORONET.pdf (2.03 MB)

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves

Download (2.03 MB)
journal contribution
posted on 2022-11-02, 16:04 authored by Oskar Wysocki, Cong Zhou, Jacobo Rogado, Prerana Huddar, Rohan Shotton, Ann Tivey, Laurence Albiges, Angelos Angelakas, Dirk Arnold, Theingi Aung, Kathryn Banfill, Mark Baxter, Fabrice Barlesi, Arnaud Bayle, Benjamin Besse, Talvinder Bhogal, Hayley Boyce, Fiona Britton, Antonio Calles, Luis Castelo-Branco, Ellen Copson, Adina Croitoru, Sourbha S Dani, Elena Dickens, Leonie Eastlake, Paul Fitzpatrick, Stephanie Foulon, Henrik Frederiksen, Sarju Ganatra, Spyridon Gennatas, Andreas Glenthoj, Fabio Gomes, Donna M Graham, Christina Hague, Kevin Harrington, Michelle Harrison, Laura Horsley, Richard Hoskins, Zoe Hudson, Lasse H Jakobsen, Nalinie Joharatnam-Hogan, Sam Khan, Umair T Khan, Khurum Khan, Alexandra Lewis, Christophe Massard, Alec Maynard, Hayley McKenzie, Olivier Michielin, Anne C Mosenthal, Berta Obispo, Carlo Palmieri, Rushin Patel, George Pentheroudakis, Solange Peters, Kimberly Rieger-Christ, Timothy Robinson, Emanuela Romano, Michael Rowe, Marina Sekacheva, Roseleen Sheehan, Alexander Stockdale, Anne Thomas, Lance Turtle, David Vinal, Jamie Weaver, Sophie Williams, Caroline Wilson, Caroline Dive, Donal Landers, Timothy Cooksley, Andre Freitas, Anne C Armstrong, Rebecca J Lee
Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants.

History

Author affiliation

Department of Health Sciences, University of Leicester

Version

  • VoR (Version of Record)

Published in

CANCERS

Volume

14

Issue

16

Pagination

(15)

Publisher

MDPI

issn

2072-6694

eissn

2072-6694

Copyright date

2022

Available date

2022-11-02

Spatial coverage

Switzerland

Language

English

Usage metrics

    University of Leicester Publications

    Categories

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC