ArticleJournal of cancer research and clinical oncology2021
An online tool for predicting the prognosis of cancer patients with SARS-CoV-2 infection: a multi-center study.
Article in Journal of cancer research and clinical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.
- Predictors of clinical evolution of SARS-CoV-2 infection in hematological patients: A systematic review and meta-analysis.Hematological oncology · 2023Pooled it
- Pooled it
- Predictors of Hospitalization due to Febrile Neutropenia in Cancer Patients Receiving Chemotherapy.Cancer medicine · 2026Observational
- Epidemiologic and Clinical Characteristics of Cancer Patients Presented to the Emergency Service with COVID-19 Symptoms.International journal of general medicine · 2025Article
- Applying the digital data and the bioinformatics tools in SARS-CoV-2 research.Computational and structural biotechnology journal · 2023Review
- Two novel nomograms for predicting the risk of hospitalization or mortality due to COVID-19 by the naïve Bayesian classifier method.Journal of medical virology · 2021Article
- Clinical Utility of a Nomogram for Predicting 30-Days Poor Outcome in Hospitalized Patients With COVID-19: Multicenter External Validation and Decision Curve Analysis.Frontiers in medicine · 2020Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
purposeDuring 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.
methodsWe 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).
resultsAmong 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.
conclusionOverall, 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.
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