Published 2022
| Version v1
Publication
A definitive prognostication system for patients with thoracic malignancies diagnosed with COVID-19: an update from the TERAVOLT registry
Creators
- Whisenant, Jennifer G
- Baena, Javier
- Cortellini, Alessio
- Huang, Li-Ching
- Lo Russo, Giuseppe
- Porcu, Luca
- Wong, Selina K
- Bestvina, Christine M
- Hellmann, Matthew D
- Roca, Elisa
- Rizvi, Hira
- Monnet, Isabelle
- Boudjemaa, Amel
- Rogado, Jacobo
- Pasello, Giulia
- Leighl, Natasha B
- Arrieta, Oscar
- Aujayeb, Avinash
- Batra, Ullas
- Azzam, Ahmed Y
- Unk, Mojca
- Azab, Mohammed A
- Zhumagaliyeva, Ardak N
- Gomez-Martin, Carlos
- Blaquier, Juan B
- Geraedts, Erica
- Mountzios, Giannis
- Serrano-Montero, Gloria
- Reinmuth, Niels
- Coate, Linda
- Marmarelis, Melina
- Presley, Carolyn J
- Hirsch, Fred R
- Garrido, Pilar
- Khan, Hina
- Baggi, Alice
- Mascaux, Celine
- Halmos, Balazs
- Ceresoli, Giovanni L
- Fidler, Mary J
- Scotti, Vieri
- Métivier, Anne-Cécile
- Falchero, Lionel
- Felip, Enriqueta
- Genova, Carlo
- Mazieres, Julien
- Tapan, Umit
- Brahmer, Julie
- Bria, Emilio
- Puri, Sonam
- Popat, Sanjay
- Reckamp, Karen L
- Morgillo, Floriana
- Nadal, Ernest
- Mazzoni, Francesca
- Agustoni, Francesco
- Bar, Jair
- Grosso, Federica
- Avrillon, Virginie
- Patel, Jyoti D
- Gomes, Fabio
- Ibrahim, Ehab
- Trama, Annalisa
- Bettini, Anna C
- Barlesi, Fabrice
- Dingemans, Anne-Marie
- Wakelee, Heather
- Peters, Solange
- Horn, Leora
- Garassino, Marina Chiara
- Torri, Valter
Contributors
Others:
- Whisenant, Jennifer G
- Baena, Javier
- Cortellini, Alessio
- Huang, Li-Ching
- Lo Russo, Giuseppe
- Porcu, Luca
- Wong, Selina K
- Bestvina, Christine M
- Hellmann, Matthew D
- Roca, Elisa
- Rizvi, Hira
- Monnet, Isabelle
- Boudjemaa, Amel
- Rogado, Jacobo
- Pasello, Giulia
- Leighl, Natasha B
- Arrieta, Oscar
- Aujayeb, Avinash
- Batra, Ulla
- Azzam, Ahmed Y
- Unk, Mojca
- Azab, Mohammed A
- Zhumagaliyeva, Ardak N
- Gomez-Martin, Carlo
- Blaquier, Juan B
- Geraedts, Erica
- Mountzios, Gianni
- Serrano-Montero, Gloria
- Reinmuth, Niel
- Coate, Linda
- Marmarelis, Melina
- Presley, Carolyn J
- Hirsch, Fred R
- Garrido, Pilar
- Khan, Hina
- Baggi, Alice
- Mascaux, Celine
- Halmos, Balaz
- Ceresoli, Giovanni L
- Fidler, Mary J
- Scotti, Vieri
- Métivier, Anne-Cécile
- Falchero, Lionel
- Felip, Enriqueta
- Genova, Carlo
- Mazieres, Julien
- Tapan, Umit
- Brahmer, Julie
- Bria, Emilio
- Puri, Sonam
- Popat, Sanjay
- Reckamp, Karen L
- Morgillo, Floriana
- Nadal, Ernest
- Mazzoni, Francesca
- Agustoni, Francesco
- Bar, Jair
- Grosso, Federica
- Avrillon, Virginie
- Patel, Jyoti D
- Gomes, Fabio
- Ibrahim, Ehab
- Trama, Annalisa
- Bettini, Anna C
- Barlesi, Fabrice
- Dingemans, Anne-Marie
- Wakelee, Heather
- Peters, Solange
- Horn, Leora
- Garassino, Marina Chiara
- Torri, Valter
Description
Background: Patients with thoracic malignancies are at increased risk for mortality from Coronavirus disease 2019 (COVID-19) and large number of intertwined prognostic variables have been identified so far. Methods: Capitalizing data from the 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, clinical COVID-19 and cancer characteristics. Results: As of April 15, 2021, 1491 consecutive evaluable 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 approximately 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 then identified seven major determinants of death 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 (CRP) (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 ROC analysis for death of the selected model confirmed its diagnostic ability (AUC 0.78; 95%CI: 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 CRP as the major determinants of prognosis. Conclusion: From 73 variables analyzed, seven major determinants of death have been identified. Poor ECOG-PS demonstrated 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.
Additional details
Identifiers
- URL
- http://hdl.handle.net/11567/1073046
- URN
- urn:oai:iris.unige.it:11567/1073046
Origin repository
- Origin repository
- UNIGE