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

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.

Keywords

• covid-19
• cancer
• comorbid pathology
• severe flow risk factors
• coronet