Diagnostic reliability of chest CT qualitative and quantitative assessment to predict survival and morbidity in oncology patients with COVID-19 infection

Abstract

Abstract Background To estimate the diagnostic utility of chest CT qualitative assessment and chest CT total severity score (TSS) to predict mortality in oncology patients with COVID-19 infection. Methods This retrospective study included 151 oncology patients with COVID-19 infection. 67, 84 were male and female, respectively. Their mean age (years) ± SD was 49.7 ± 14.9. Two radiologists individually reviewed the chest CT and scored the pulmonary abnormalities using TSS. Inter-observer agreement was determined using the Bland–Altman plot. Correlation between TSS and COVID-19 severity, complication, mortality, cancer status and effect in anticancer therapy plan was done. Results There was a statistically significant excellent agreement between the independent observers in quantitative pulmonary assessment using TSS with interclass correlation (ICC) > 0.9 (P < 0.001). ROC curve analysis revealed that TSS was statistically significantly higher in non-survivors using an optimum cut-off value of 5 to predict in-hospital mortality. Univariate analysis showed that age, pulmonary predominant pattern, pleural effusion, tree-in-bud, ECOG PS, tumour stage 4 and post-COVID cancer status were a statistically significant predictor of mortality. Multivariate analysis reported that consolidation versus ground-glass opacity (GGO), crazy paving pattern versus GGO and progressive versus remittent cancer diseases were statistically significant independent predictors of mortality among those patients. Conclusions TSS demonstrated excellent inter-observer agreement to assess COVID-19 in oncology patients with low cut-off value to predict in-hospital mortality, thus raising the attention to rapid proper care in this setting. There was a statistically significant positive correlation between TSS and delayed chemotherapeutic schedule.