TY - JOUR AU - Wysocki, Oskar AU - Zhou, Cong AU - Rogado, Jacobo AU - Huddar, P. AU - Shotton, Rohan AU - Tivey, Ann AU - Albiges, Laurence AU - Angelakas, Angelos AU - Arnold, Dirk AU - Aung, Theingi AU - Banfill, Kathryn AU - Baxter, Mark A.J. AU - Barlesi, Fabrice AU - Bayle, Arnaud AU - Besse, Benjamin AU - Bhogal, Talvinder AU - Boyce, Hayley AU - Britton, Fiona AU - Calles, Antonio AU - Castelo-Branco, Luis AU - Copson, Ellen AU - Croitoru, Adina E. AU - Dani, Sourbha S. AU - Dickens, Elena AU - Eastlake, Leonie AU - Fitzpatrick, Paul AU - Foulon, Stephanie AU - Frederiksen, Henrik AU - Ganatra, Sarju AU - Gennatas, Spyridon AU - Glenthøj, Andreas AU - Gomes, Fabio AU - Graham, Donna M. AU - Hague, Christina AU - Harrington, Kevin AU - Harrison, Michelle AU - Horsley, L. AU - Hoskins, Richard AU - Hudson, Zoe AU - Jakobsen, Lasse H. AU - Khan, Sam AU - Khan, Umair T. AU - Khan, Khurram Shahzad AU - Lewis, Alexandra AU - Massard, Christophe AU - Maynard, Alec AU - McKenzie, Hayley AU - Michielin, Olivier AU - Mosenthal, Anne C. AU - Obispo, Berta AU - Palmieri, Carlo AU - Patel, Rushin AU - Pentheroudakis, George AU - Peters, Solange AU - Rieger-Christ, Kimberly AU - Robinson, Timothy AU - Romano, Emanuela AU - Rowe, Michael AU - Sekacheva, Marina AU - Sheehan, Roseleen AU - Stockdale, Alexander J. AU - Thomas, Anne AU - Turtle, Lance C.W. AU - Viñal, David AU - Weaver, Jamie AU - Williams, Sophie AU - Wilson, Caroline AU - Dive, Caroline AU - Landers, Donal AU - Cooksley, Timothy AU - Freitas, André AU - Armstrong, Anne C. AU - Lee, Rebecca J. AU - ESMO Co-Care PY - 2022 DA - August TI - An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves JO - Cancers VL - 14 IS - 16 DO - https://doi.org/10.3390/cancers14163931 AB - 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. PB - MDPI UR - https://discovery.dundee.ac.uk/en/publications/0e966f68-5cc5-4214-97ba-e7ff33ab93cf KW - Coronavirus (COVID-19) ER