ArticleJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2022
A Definitive Prognostication System for Patients With Thoracic Malignancies Diagnosed With Coronavirus Disease 2019: An Update From the TERAVOLT Registry.
Article in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 20 citations in OpenAlex.
- COVID-19 vaccine effectiveness in patients with lung cancer: challenges in the Omicron era.BMC infectious diseases · 2026Article
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- Eosinopenia predicts poor outcomes in patients with lung cancer with the omicron variant of COVID-19.Frontiers in medicine · 2025Article
- Brief Report: Impact of Anti-Cancer Treatments on Outcomes of COVID-19 in Patients With Thoracic Cancers: A CCC19 Registry Analysis.Clinical lung cancer · 2024Article
- COVID-19 in patients with thymic epithelial tumors with or without Good's syndrome: a single-center retrospective study.BMC cancer · 2024Article
- ACE2: the node connecting the lung cancer and COVID-19.American journal of cancer research · 2024Review
- Mortality rates from asbestos-related diseases in Italy during the first year of the COVID-19 pandemic.Frontiers in public health · 2023Article
- Radiation-Induced Lung Injury: Prevention, Diagnostics and Therapy in the Era of the COVID-19 Pandemic.Journal of clinical medicine · 2022Article
- Coronavirus Disease 2019 Outcomes, Patient Vaccination Status, and Cancer-Related Delays During the Omicron Wave: A Brief Report From the TERAVOLT Analysis.JTO clinical and research reports · 2022Article
- Delayed visit and treatment of lung cancer during the coronavirus disease 2019 pandemic in Japan: a retrospective study.The Journal of international medical research · 2022Article
- How SOLID is the immune system's response to the deadly duo of lung cancer and SARS-CoV-2?Translational lung cancer research · 2022Article
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72 authors at 20 institutions in 18 countries.
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Abstract
introductionPatients with thoracic malignancies are at increased risk for mortality from coronavirus disease 2019 (COVID-19), and a large number of intertwined prognostic variables have been identified so far.
methodsCapitalizing data from the Thoracic Cancers International COVID-19 Collaboration (TERAVOLT) registry, a global study created with the aim of describing the impact of COVID-19 in patients with thoracic malignancies, we used a clustering approach, a fast-backward step-down selection procedure, and a tree-based model to screen and optimize a broad panel of demographics and clinical COVID-19 and cancer characteristics.
resultsAs of April 15, 2021, a total of 1491 consecutive eligible patients from 18 countries were included in the analysis. With a mean observation period of 42 days, 361 events were reported with an all-cause case fatality rate of 24.2%. The clustering procedure screened 73 covariates in 13 clusters. A further multivariable logistic regression for the association between clusters and death was performed, resulting in five clusters significantly associated with the outcome. The fast-backward step-down selection procedure then identified the following seven major determinants of death: Eastern Cooperative Oncology Group-performance status (ECOG-PS) (OR = 2.47, 1.87-3.26), neutrophil count (OR = 2.46, 1.76-3.44), serum procalcitonin (OR = 2.37, 1.64-3.43), development of pneumonia (OR = 1.95, 1.48-2.58), C-reactive protein (OR = 1.90, 1.43-2.51), tumor stage at COVID-19 diagnosis (OR = 1.97, 1.46-2.66), and age (OR = 1.71, 1.29-2.26). The receiver operating characteristic analysis for death of the selected model confirmed its diagnostic ability (area under the receiver operating curve = 0.78, 95% confidence interval: 0.75-0.81). The nomogram was able to classify the COVID-19 mortality in an interval ranging from 8% to 90%, and the tree-based model recognized ECOG-PS, neutrophil count, and c-reactive protein as the major determinants of prognosis.
conclusionsFrom 73 variables analyzed, seven major determinants of death have been identified. Poor ECOG-PS was found to have the strongest association with poor outcome from COVID-19. With our analysis, we provide clinicians with a definitive prognostication system to help determine the risk of mortality for patients with thoracic malignancies and COVID-19.
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