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    An international comparison of presentation, outcomes and coronet predictive score performance in patients with cancer presenting with COVID-19 across different pandemic waves

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    Authors
    Wysocki, Oskar
    Zhou, Cong
    Rogado, J.
    Huddar, Prerana
    Shotton, Rohan
    Tivey, Ann
    Albiges, L.
    Angelakas, Angelos
    Arnold, D.
    Aung, T.
    Banfill, Kathryn
    Baxter, M.
    Barlesi, F.
    Bayle, A.
    Besse, B.
    Bhogal, T.
    Boyce, H.
    Britton, Fiona
    Calles, A.
    Castelo-Branco, L.
    Copson, E.
    Croitoru, A.
    Dani, S. S.
    Dickens, E.
    Eastlake, L.
    Fitzpatrick, Paul
    Foulon, S.
    Frederiksen, H.
    Ganatra, S.
    Gennatas, S.
    Glenthøj, A.
    Gomes, Fabio
    Graham, Donna
    Hague, Christina
    Harrington, K.
    Harrison, M.
    Horsley, Laura
    Hoskins, R.
    Hudson, Z.
    Jakobsen, L. H.
    Joharatnam-Hogan, N.
    Khan, S.
    Khan, U. T.
    Khan, K.
    Lewis, Alexandra R
    Massard, C.
    Maynard, A.
    McKenzie, H.
    Michielin, O.
    Mosenthal, A. C.
    Obispo, B.
    Palmieri, C.
    Patel, R.
    Pentheroudakis, G.
    Peters, S.
    Rieger-Christ, K.
    Robinson, T.
    Romano, E.
    Rowe, M.
    Sekacheva, M.
    Sheehan, R.
    Stockdale, A.
    Thomas, A.
    Turtle, L.
    Viñal, D.
    Weaver, Jamie M
    Williams, S.
    Wilson, C.
    Dive, Caroline
    Landers, Donal
    Cooksley, Timothy J
    Freitas, Andre
    Armstrong, Anne C
    Lee, Rebecca J
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    Affiliation
    Department of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK
    Issue Date
    2022
    
    Metadata
    Show full item record
    Abstract
    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.
    Citation
    Wysocki O, Zhou C, Rogado J, Huddar P, Shotton R, Tivey A, et al. An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves. Cancers (Basel). 2022 Aug 16;14(16). PubMed PMID: 36010932. Pubmed Central PMCID: PMC9406013. Epub 2022/08/27. eng.
    Journal
    Cancers
    URI
    http://hdl.handle.net/10541/625601
    DOI
    10.3390/cancers14163931
    PubMed ID
    36010932
    Additional Links
    https://dx.doi.org/10.3390/cancers14163931
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.3390/cancers14163931
    Scopus Count
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