CORONET online risk assessment tool and Charlson comorbidity index in predicting fatalities in cancer patients with COVID-19 - A. S. Rusanov; M. I. Sekacheva; A. A. Tyazhelnikov (Исследования и практика в медицине)
Purpose of the study. Сomparing and evaluating the prognostic potential of the CORONET online risk assessment tool and the Charlson Comorbidity Index in predicting mortality in cancer patients with COVID-19.Materials and methods. The results are drawn from the data of 168 case histories of cancer patients who were undergoing inpatient treatment for COVID-19 at the University Clinical Hospitals of Sechenov University between March 2020 and February 2022. The study was conducted as part of the program of the world-class research center “Digital Biodesign and Personalized Healthcare” of Sechenov University, with participation in the ESMO-CoCARE Registry project. Patients with a history of solid or hematologic malignancies were included in the study; their treatment period before the study was 5 years or less. The age ranged from 37 to 100 years, the median age was 69 years. The CORONET online risk assessment tool and the Charlson comorbidity index were used to objectify the severity of multimorbidity status and prognosis of fatal outcomes in cancer patients with COVID-19.Results. It was demonstrated that statistically significant effects on the prognosis of mortality in patients with cancer were: age, percentage of saturation on admission, treatment in intensive care units (ICU), National Early Warning Score 2 (NEWS2) distress syndrome severity scale score, computed tomography (CT) assessment of disease course severity, decreased blood albumin and platelet counts, and increased blood neutrophil counts in both categorical and immediate indicator value formats. In addition, it was determined that as the number of comorbidities increased, the probability of mortality increased significantly, odds ratio (OR) = 2.162 (CI 95 % 1.016–4.600; p = 0.045). The CORONET calculator score yields one of the highest OR values among all established statistically significant predictors, 20.410 (CI 95 % 4.894–85.113; p < 0.001). For oncopathology in COVID-19 patients, the Charlson index score shows statistical significance as a predictor of mortality, OR =1.396 (CI 9 5 % 1.105–1.765; p = 0.005).Conclusion. The obtained advantages in using the CORONET online decision support tool over the Charlson comorbidity index in predicting mortality in cancer patients with COVID-19 are recognized as convincing.