A definitive prognostication system for patients with thoracic malignancies diagnosed with COVID-19: an update from the TERAVOLT registry.
View/ Open
Date
2022-01-24ICR Author
Author
Whisenant, JG
Baena, J
Cortellini, A
Huang, L-C
Lo Russo, G
Porcu, L
Wong, SK
Bestvina, CM
Hellmann, MD
Roca, E
Rizvi, H
Monnet, I
Boudjemaa, A
Rogado, J
Pasello, G
Leighl, NB
Arrieta, O
Aujayeb, A
Batra, U
Azzam, AY
Unk, M
Azab, MA
Zhumagaliyeva, AN
Gomez-Martin, C
Blaquier, JB
Geraedts, E
Mountzios, G
Serrano-Montero, G
Reinmuth, N
Coate, L
Marmarelis, M
Presley, CJ
Hirsch, FR
Garrido, P
Khan, H
Baggi, A
Mascaux, C
Halmos, B
Ceresoli, GL
Fidler, MJ
Scotti, V
Métivier, A-C
Falchero, L
Felip, E
Genova, C
Mazieres, J
Tapan, U
Brahmer, J
Bria, E
Puri, S
Popat, S
Reckamp, KL
Morgillo, F
Nadal, E
Mazzoni, F
Agustoni, F
Bar, J
Grosso, F
Avrillon, V
Patel, JD
Gomes, F
Ibrahim, E
Trama, A
Bettini, AC
Barlesi, F
Dingemans, A-M
Wakelee, H
Peters, S
Horn, L
Garassino, MC
Torri, V
TERAVOLT study group
Type
Journal Article
Metadata
Show full item recordAbstract
<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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.
Collections
Subject
TERAVOLT study group
Research team
Thoracic Oncology
Language
eng
Date accepted
2021-12-31
License start date
2022-01-24
Citation
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2022