ABSTRACT
Purpose: During the coronavirus disease 2019 (COVID-19) pandemic, oncologists face new challenges and they need to adjust their cancer management strategies as soon as possible to reduce the risk of SARS-CoV-2 infection and tumor recurrence. However, data on cancer patients with SARS-CoV-2 infection remains scarce. Methods: We performed a retrospective study of 223 cancer patients with SARS-CoV-2 from 26 hospitals in Hubei, China. An individualized nomogram was constructed based on multivariable Cox analysis. Considering the convenience of the nomogram application, an online tool was also created by shiny app. C-index, calibration curves and decision curve analysis (DCA) were performed to verify the prediction performance and clinical application of the nomogram.Results: Among cancer patients with SARS-CoV-2, there were significant differences in clinical characteristics between survivors and non-survivors, and lung cancer patients had similar short-time survival with other cancer patients. Male, dyspnea, elevated PCT, increased heart rate, elevated D-dimers, decreased platelets and so on were risk factors for these patients. Furthermore, good prediction performance of the online tool (dynamic nomogram: https://covid-19-prediction-tool.shinyapps.io/DynNomapp/). was also fully demonstrated with the C-index of 0.841 (95% CI: 0.782 - 0.900) in the development cohort and 0.780 (95% CI: 0.678-0.882) in the validation cohort. Conclusion: Overall, cancer patients with SARS-CoV-2 had unique clinical features, and the established online tool could guide clinicians to predict the prognosis of patients and to develop more rational treatment strategies for cancer patients during the COVID-19 epidemic.