{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Whisenant JG"],"funding":["NCI NIH HHS","International Association for the Study of Lung Cancer"],"pagination":["661-674"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8804493"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["17(5)"],"pubmed_abstract":["<h4>Introduction</h4>Patients 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.<h4>Methods</h4>Capitalizing 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.<h4>Results</h4>As of April 15, 2021, a total of 1491 consecutive eligible patients from 18 countries were included in the analysis. With a mean obs"],"journal":["Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer"],"pubmed_title":["A Definitive Prognostication System for Patients With Thoracic Malignancies Diagnosed With Coronavirus Disease 2019: An Update From the TERAVOLT Registry."],"pmcid":["PMC8804493"],"funding_grant_id":["UG1 CA233290","P30 CA008748"],"pubmed_authors":["Porcu L","Geraedts E","Mazzoni F","Brahmer J","Hirsch FR","Garassino MC","Felip E","Coate L","Pasello G","Peters S","Hellmann MD","Azab MA","Bar J","Torri V","Azzam AY","TERAVOLT study group","Monnet I","Bestvina CM","Genova C","Marmarelis M","Unk M","Horn L","Trama A","Barlesi F","Baena J","Ibrahim E","Ceresoli GL","Fidler MJ","Zhumagaliyeva AN","Aujayeb A","Mascaux C","Garrido P","Wakelee H","Mazieres J","Bria E","Huang LC","Morgillo F","Wong SK","Rizvi H","Agustoni F","Gomes F","Tapan U","Scotti V","Rogado J","Cortellini A","Mountzios G","Baggi A","Dingemans AM","Roca E","Gomez-Martin C","Nadal E","Grosso F","Batra U","Popat S","Serrano-Montero G","Metivier AC","Puri S","Arrieta O","Whisenant JG","Khan H","Halmos B","Boudjemaa A","Blaquier JB","Reinmuth N","Bettini AC","Presley CJ","Reckamp KL","Avrillon V","Lo Russo G","Leighl NB","Patel JD","Falchero L"],"additional_accession":[]},"is_claimable":false,"name":"A Definitive Prognostication System for Patients With Thoracic Malignancies Diagnosed With Coronavirus Disease 2019: An Update From the TERAVOLT Registry.","description":"<h4>Introduction</h4>Patients 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.<h4>Methods</h4>Capitalizing 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.<h4>Results</h4>As of April 15, 2021, a total of 1491 consecutive eligible patients from 18 countries were included in the analysis. With a mean obs","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 May","modification":"2025-04-03T21:30:07.68Z","creation":"2025-04-03T21:30:07.68Z"},"accession":"S-EPMC8804493","cross_references":{"pubmed":["35121086"],"doi":["10.1016/j.jtho.2021.12.015"]}}