An online tool for predicting the prognosis of cancer patients with SARS-CoV-2 infection: a multi-center study
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ORIGINAL ARTICLE – CLINICAL ONCOLOGY
An online tool for predicting the prognosis of cancer patients with SARS‑CoV‑2 infection: a multi‑center study Congkuan Song1,2 · Zhe Dong1 · Hongyun Gong3 · Xiao‑Ping Liu4 · Xiaorong Dong5 · Aifen Wang6 · Yuan Chen7 · Qibin Song3 · Weidong Hu1,2 Received: 29 June 2020 / Accepted: 3 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Purpose During the 2019 coronavirus disease (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 conducted a retrospective study on 223 cancer patients with SARS-CoV-2 from 26 hospitals in Hubei, China. An individualized nomogram was constructed based on multivariate Cox analysis. Considering the convenience of the nomogram application, an online tool was also created. The predictive performance and clinical application of nomogram were verified by C-index, calibration curve and decision curve analysis (DCA). Results Among cancer patients with SARS-CoV-2, there were significant differences in clinical characteristics between survivors and non-survivors, and compared with patients with solid tumors including lung cancer, patients with hematological malignancies had a worse prognosis. Male, dyspnea, elevated PCT, increased heart rate, elevated D-dimers, and decreased platelets were risk factors for these patients. Furthermore, a good prediction performance of the online tool (dynamic nomogram: https://covid-19-prediction-tool.shinyapps.io/DynNomapp/) was also fully demonstrated with the C-indexes 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 during the COVID-19 epidemic and to develop more rational treatment strategies for cancer patients. Keywords Cancer · COVID-19 · SARS-CoV-2 · Nomogram · Prognosis
Introduction
Congkuan Song, Zhe Dong and Hongyun Gong contributed equally to this study. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00432-020-03420-6) contains supplementary material, which is available to authorized users. * Yuan Chen [email protected] * Qibin Song [email protected] * Weidong Hu [email protected] Extended author information available on the last page of the article
Since the outbreak of coronavirus disease (COVID-19) in December 2019, the number of infected cases has been increasing, which has seriously affected the normal life of human beings. Recently, increased studies have suggested that cancer patients were more susceptible to SARSCoV-2 infection (Dai et al. 2020; Liang et al. 2020). Thus, oncologists face the new challenge during the COVID-19 pandemic. They need
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