ABSTRACT
Introduction: The Thoracic Centers International coronavirus disease 2019 (COVID-19) Collaboration (TERAVOLT) registry found approximately 30% mortality in patients with thoracic malignancies during the initial COVID-19 surges. Data from South Africa suggested a decrease in severity and mortality with the Omicron wave. Our objective was to assess mortality of patients with thoracic malignancies with the Omicron-predominant wave and evaluate efficacy of vaccination. Methods: A prospective, multicenter observational study was conducted. A total of 28 institutions contributed data from January 14, 2022, to February 4, 2022. Inclusion criteria were any thoracic cancer and a COVID-19 diagnosis on or after November 1, 2021. End points included mortality, hospitalization, symptomatic COVID-19 infection, asymptomatic COVID-19 infection, and delay in cancer therapy. Analysis was done through contingency tables and a multivariable logistic model. Results: We enrolled a total of 346 patients. Median age was 65 years, 52.3% were female, 74.2% were current or former smokers, 86% had NSCLC, 72% had stage IV at time of COVID-19 diagnosis, and 66% were receiving cancer therapy. Variant was unknown for 70%; for those known, Omicron represented 82%. Overall mortality was 3.2%. Using multivariate analysis, COVID-19 vaccination with booster compared with no vaccination had a protective effect on hospitalization or death (OR = 0.30, confidence interval: 0.15-0.57, p = 0.0003), whereas vaccination without booster did not (OR = 0.64, confidence interval: 0.33-1.24, p = 0.1864). Cancer care was delayed in 56.4% of the patients. Conclusions: TERAVOLT found reduced patient mortality with the most recent COVID-19 surge. COVID-19 vaccination with booster improved outcomes of hospitalization or death. Delays in cancer therapy remain an issue, which has the potential to worsen cancer-related mortality.
ABSTRACT
INTRODUCTION: 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. METHODS: 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. RESULTS: As 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. CONCLUSIONS: From 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.