Comorbid pathology in SARS-CoV-2 infected in cancer practice as a predictor of severe outcomes in COVID-19. COVID-19 prognostic online risk assessment tool in oncology: A retrospective study

Q4 Medicine
M. Sekacheva, Alexander S. Rusanov, I. I. Kokhanovskaia
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Abstract

Aim. Evaluation of comorbid pathology in SARS-CoV-2 infected in cancer practice as a predictor of severe outcomes. Testing the COVID-19 risk assessment tool in oncology (CORONET), to predict the likely severity of COVID-19 course in cancer patients on inpatient treatment. Materials and methods. A retrospective analysis of 173 cancer patient disease stories was conducted. The study was conducted as part of the program of the World-Class Research Center “Digital Biodesine and Personalized Health Care” of the University of Sechenov, with participation in the ESMO-CoCARE Register project. Based on the ESMO COVID-19 and CAncerREgistry (ESMO-CoCARE) registry, taking into account the entered our patient sample (n=173), a COVID-19 risk assessment tool in oncology (CORONET) was developed. Results. Cancer patients with comorbid pathology have been shown to have an increased risk of COVID-19 course of the disease from this sample by CORONET (mean conclusion score CORONET 2.44 pointsseverity). Prognosis of probable severity of outcomes in cancer patients infected with SARS-CoV-2 depends on associated diseases. The presence of a history of ≥3 comorbid pathologies in COVID-19 patients was detected in 106 people (61.27%). 15 patients were included in the risk of severe course. Retrospective analysis obtained actual confirmation of the prognosis of severe course of the disease in this group followed by death in all these patients (71.42% of all deaths). Indicators such as low albumin levels, high levels of C-reactive protein and neutrophils showed high prognostic significance of the likely severity of coronavirus infection in cancer patients on inpatient treatment for COVID-19. The mortality rate of patients admitted with COVID-19 and cancer was 12.14%. Conclusion. The most informative predictors of severe outcomes in COVID-19 in inpatient cancer patients to assess the prognosis of disease severity are: number of comorbidities, age, NEWS2 scale, ECOG patient activity status, albumin level, C-reactive protein level and absolute neutrophil level. The benefits gained in the use of the online decision support tool CORONET are considered convincing not only during the decision-making phase of hospitalization, but also in cancer patients on inpatient treatment.
COVID-19中作为严重后果预测因素的SARS-CoV-2癌症感染者的合并病理变化。COVID-19肿瘤预后在线风险评估工具:回顾性研究
目的评估癌症患者感染 SARS-CoV-2 后的合并病理情况,以预测严重后果。测试肿瘤学 COVID-19 风险评估工具 (CORONET),以预测住院治疗的癌症患者 COVID-19 病程的可能严重程度。材料与方法对 173 名癌症患者的病情进行了回顾性分析。该研究是塞切诺夫大学 "数字生物碱和个性化医疗 "世界级研究中心计划的一部分,参与了ESMO-CoCARE注册项目。在ESMO COVID-19和CAncerREgistry(ESMO-CoCARE)登记处的基础上,考虑到我们输入的患者样本(n=173),开发了肿瘤学COVID-19风险评估工具(CORONET)。结果显示从CORONET的样本来看,合并病理的癌症患者COVID-19病程风险增加(CORONET平均结论得分2.44分严重性)。感染 SARS-CoV-2 的癌症患者的预后可能严重程度取决于相关疾病。在 COVID-19 患者中,有 106 人(61.27%)存在≥3 种合并病史。15名患者被纳入严重病程风险中。回顾性分析证实了这组患者的严重病程预后,所有这些患者均死亡(占死亡总数的 71.42%)。低白蛋白水平、高水平的 C 反应蛋白和中性粒细胞等指标显示,在接受 COVID-19 住院治疗的癌症患者中,冠状病毒感染的可能严重程度具有很高的预后意义。COVID-19 和癌症患者的死亡率为 12.14%。结论在评估癌症住院患者 COVID-19 严重后果的预后时,最有参考价值的预测因素包括:合并症数量、年龄、NEWS2 量表、ECOG 患者活动状态、白蛋白水平、C 反应蛋白水平和绝对中性粒细胞水平。使用在线决策支持工具 CORONET 所带来的益处不仅在住院决策阶段,而且在住院治疗的癌症患者中都是令人信服的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Modern Oncology
Journal of Modern Oncology Medicine-Oncology
CiteScore
0.50
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0.00%
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审稿时长
5 weeks
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