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不同疫情波次中合并COVID-19的癌症患者的临床表现、结局及CORONET预测评分表现的国际比较

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

作者信息

Wysocki Oskar, Zhou Cong, Rogado Jacobo, Huddar Prerana, Shotton Rohan, Tivey Ann, Albiges Laurence, Angelakas Angelos, Arnold Dirk, Aung Theingi, Banfill Kathryn, Baxter Mark, Barlesi Fabrice, Bayle Arnaud, Besse Benjamin, Bhogal Talvinder, Boyce Hayley, Britton Fiona, Calles Antonio, Castelo-Branco Luis, Copson Ellen, Croitoru Adina, Dani Sourbha S, Dickens Elena, Eastlake Leonie, Fitzpatrick Paul, Foulon Stephanie, Frederiksen Henrik, Ganatra Sarju, Gennatas Spyridon, Glenthøj Andreas, Gomes Fabio, Graham Donna M, Hague Christina, Harrington Kevin, Harrison Michelle, Horsley Laura, Hoskins Richard, Hudson Zoe, Jakobsen Lasse H, Joharatnam-Hogan Nalinie, Khan Sam, Khan Umair T, Khan Khurum, Lewis Alexandra, Massard Christophe, Maynard Alec, McKenzie Hayley, Michielin Olivier, Mosenthal Anne C, Obispo Berta, Palmieri Carlo, Patel Rushin, Pentheroudakis George, Peters Solange, Rieger-Christ Kimberly, Robinson Timothy, Romano Emanuela, Rowe Michael, Sekacheva Marina, Sheehan Roseleen, Stockdale Alexander, Thomas Anne, Turtle Lance, Viñal David, Weaver Jamie, Williams Sophie, Wilson Caroline, Dive Caroline, Landers Donal, Cooksley Timothy, Freitas André, Armstrong Anne C, Lee Rebecca J

机构信息

Department of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK.

Digital Experimental Cancer Medicine Team, Cancer Biomarker Centre, Cancer Research UK Manchester Institute, University of Manchester, Alderley Park, Macclesfield SK10 4TG, UK.

出版信息

Cancers (Basel). 2022 Aug 16;14(16):3931. doi: 10.3390/cancers14163931.

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.

摘要

癌症患者感染新冠病毒后病情加重的风险已被证实有所增加。我们之前构建并验证了肿瘤学新冠风险评估工具(CORONET),以预测因患活动性癌症而入院的患者感染新冠病毒后可能出现的严重程度。我们评估了不同疫情阶段癌症合并新冠病毒感染患者的临床表现和预后差异。我们研究了全球范围内不同疫情阶段患者在临床表现特征和预后方面的差异:第1波D614G毒株(n = 1430)、第2波阿尔法毒株(n = 475)以及第4波仅来自英国和西班牙的奥密克戎变异株(n = 63)。分别对每一波的258例、48例和54例患者评估了CORONET的性能。我们发现后续疫情阶段的死亡率有所降低。在第4波疫情中,大多数患者接种了疫苗,94% 需要吸氧的患者接受了类固醇治疗。癌症分期和患者的中位年龄有显著差异,但与新冠病毒感染不良预后相关的特征仍然具有预测性,且在不同疫情阶段没有差异。CORONET工具在所有疫情阶段均表现良好,曲线下面积(AUC)得分>0.72。我们得出结论,因感染新冠病毒而入院的癌症患者具有相似的严重程度特征,尽管病毒变异株和疫苗接种状况存在差异,但这些特征仍然具有区分性。在第一波疫情之后生存率有所提高,这可能与疫苗接种以及对需要吸氧的患者增加使用类固醇有关。CORONET模型表现良好,与严重急性呼吸综合征冠状病毒2(SARS-CoV-2)变异株无关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6ec/9406013/b0d6eeaa1438/cancers-14-03931-g001.jpg

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