A Definitive Prognostication System for Patients With Thoracic Malignancies Diagnosed With Coronavirus Disease 2019: An Update From the TERAVOLT Registry

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.

Keywords: COVID-19; Cancer; NSCLC; Registry; TERAVOLT; Thoracic.

Figure 1

Consort flow diagram for the included population. COVID-19, coronavirus disease 2019; RT-PCR, reverse-transcriptase polymerase chain reaction.

Figure 2

Prognostic nomogram including the following major determinants of mortality: occurrence of pneumonia (yes versus no), age (≤65 versus >65 y old), neutrophil count (> versus ≤ ULN), procalcitonin (> versus ≤ ULN), C-reactive protein (> versus ≤ ULN), ECOG-PS (≥2 versus 0–1), and disease stage at COVID-19 (stage IV versus stages I–III). The nomogram is able to classify the COVID-19 mortality risk in an interval ranging from 8% to 90%. In the nomogram, the determinants of mortality are represented with two symbols. On one hand, ○ represents the presence of this predictor. On the other hand, the symbol ♦ reveals the absence of it. The sum of the different determinants establishes the risk of death. COVID-19, coronavirus disease 2019; ECOG-PS, Eastern Cooperative Oncology Group—performance status; ULN, upper limit of normal.

Figure 3

Sankey diagram offering a visual expression of the CART analysis with the hierarchical classification of variables. The first node was split on the basis of ECOG-PS (0–1: 1120 patients versus ≥2: 371 patients). Among the patients with an ECOG-PS of 0 to 1, the second split was defined by serum CRP (normal: 741 patients versus high: 379 patients), whereas among the patients with an ECOG-PS of greater than or equal to 2, by neutrophil count (normal: 269 patients versus high: 102 patients). Third-generation splits were defined by tumor stage at COVID-19 diagnosis among the patients with neutrophil count > ULN (stages I–III: 26 patients with a CFR of 38.5% versus stage IV: 76 patients with a CFR of 64.5%), by serum PCT among patients with CRP > ULN (PCT normal: 302 patients with a CFR of 25.7% versus PCT high: 77 patients with a CFR of 50.5%), and by radiological finding of pneumonia among patients with CRP less than or equal to ULN and with neutrophil count less than or equal to ULN (pneumonia present: 224 with a CFR of 25.7% and 50.5%, respectively, versus pneumonia absent: 786 patients with a CFR of 8.2% and 31.1%, respectively). Diagram created using SankeyMATIC web tool (available at: https://sankeymatic.com/). Patients with missing values were included as reference terms. CART, classification and regression tree; CFR, case fatality rate; CRP, C-reactive protein; ECOG-PS, Eastern Cooperative Oncology Group—performance status; PCT, procalcitonin; ULN, upper limit of normal.