key: cord-0714077-r4xbt22i authors: 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 title: A definitive prognostication system for patients with thoracic malignancies diagnosed with COVID-19: an update from the TERAVOLT registry. date: 2022-02-01 journal: J Thorac Oncol DOI: 10.1016/j.jtho.2021.12.015 sha: ed41b2c171dea597461ea95c4482cd8c0c52e90a doc_id: 714077 cord_uid: r4xbt22i 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. 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 Keywords: COVID-19, cancer, mortality, thoracic, NSCLC, TERAVOLT, registry. In this study, we presented a comprehensive analysis with a definitive prognostic 10 stratification of the TERAVOLT study population, which has been updated and further 11 implemented with new data 16,17 . Our aim was to provide a more comprehensive prognostic model 14 Acknowledging the competing influence of the underlying thoracic malignancy in 15 determining mortality within the medium-longer term, we attempted at a possible distinction of 16 acute, likely COVID-19 related deaths from later, likely cancer-related deaths as already done 17 elsewhere 18, 19 . In doing that, we elected mortality within the observation period (from COVID-19 18 diagnosis to death/last follow-up) as clinical endpoint of interest. Considering the study design, which was not developed for reporting long-term outcomes, a dichotomized endpoint allowed us 20 to discriminate early deaths (e.g., death during hospitalization) as opposed to alive/discharged 21 patients who were considered censored with respect to COVID-19 related mortality. In view of the registry design, which was not developed to evaluate long-term outcomes, allowing providers an impartial patient assessment prior to prescribing care. To that purpose, we developed both the inference tree and the prognostic nomogram. The We acknowledge that a weakness in the current study is the timeframe by which data The ongoing efforts including immunization campaigns and enhanced capacity will likely 9 allow a progressive return to normal on a global scale. Despite that, SARS-CoV-2 will still impact 10 the continuity of care of patients with cancer, given to the evolutionary nature of pandemics, 11 vaccine hesitancy or access to it in low-income countries, and emerging new viral strains which 12 may trigger immune-escape mechanisms 52-55 . Against this evolving scenario, a more tailored, 13 comprehensive, and properly powered prognostication system like the one presented in this study 14 will be a useful tool for clinicians as they develop oncology treatment plans for their patients. All authors contributed to the publication according to the ICMJE guidelines for the authorship. All 29 authors read and approved the submitted version of the manuscript (and any substantially 30 modified version that involves the author's contribution to the study). Each author has agreed both 31 to be personally accountable for the author's own contributions and to ensure that questions 32 related to the accuracy or integrity of any part of the work, even ones in which the author was not 33 personally involved, are appropriately investigated, resolved, and the resolution documented in 34 the literature. The first, last and corresponding authors had full access to the data and final responsibility to 36 submit for publication. The CREDIT statement for authors' contributions is provided as supplementary material. The datasets generated during and/or analysed during the current study are not publicly available 2 due to privacy and ethical restrictions but are available from the corresponding author and the 3 study steering committee on reasonable request, under a relevant data sharing agreement with 4 the coordinating center. (Stage IV vs Stage I-III). The nomogram is able to classify the COVID-4 19 mortality risk in an interval ranging from 8% to 90%. In the nomogram the determinants of 5 mortality are represented with two symbols. On one hand, • represents the presence of this 6 predictor. On the other hand, the symbol ♦ shows the absence of it. The sum of the different 7 determinants stablishes the risk of death. 8 9 Figure 3 : Sankey diagram offering a visual expression of the CART analysis with the hierarchical Currently undergoing anti-cancer treatment Cancer patients in SARS-CoV-2 infection: a nationwide 9 analysis in China Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected 11 Pneumonia in Wuhan Risk of COVID-19 for patients with cancer Risk of COVID-19 for patients with cancer Clinical characteristics of COVID-19-infected cancer patients: 18 a retrospective case study in three hospitals within Wuhan COVID-19 and cancer registries: learning from the first peak of the 21 SARS-CoV-2 pandemic Abstract S12-03: Thoracic cancers 24 international COVID-19 collaboration (TERAVOLT): Small-cell lung cancer and other rare 25 thoracic malignancies COVID-19 in patients with thoracic 28 malignancies (TERAVOLT): first results of an international, registry-based COVID-19 mortality in patients with cancer on 31 chemotherapy or other anticancer treatments: a prospective cohort study COVID-19 prevalence and mortality in patients with 34 cancer and the effect of primary tumour subtype and patient demographics: a prospective 35 cohort study Clinical portrait of the SARS-CoV-2 1 epidemic in European cancer patients. Cancer Discov Thoracic Cancers International 4 COVID-19 Collaboration Supporting Clinical Decision-Making during the 7 SARS-CoV-2 Pandemic through a Global Research Commitment: The TERAVOLT Research electronic data 10 capture (REDCap)--a metadata-driven methodology and workflow process for providing 11 translational research informatics support The Eighth Edition AJCC Cancer Staging Manual: 14 Continuing to build a bridge from a population-based to a more "personalized" approach to 15 cancer staging Impact of PD-1 17 Blockade on Severity of COVID-19 in Patients with Lung Cancers. Cancer Discov COVID-19 in patients with lung cancer Determinants of enhanced vulnerability to coronavirus 22 disease 2019 in UK patients with cancer: a European study Time-Dependent COVID-19 Mortality in 25 Patients With Cancer: An Updated Analysis of the OnCovid Registry A principal components-based clustering method to identify 28 variants associated with complex traits Regression Modeling Strategies. R package version 6.2-0 Classification and regression trees R: a language and environment for statistical computing Telemedicine for cancer patients during 5 COVID-19 pandemic: between threats and opportunities Severity of COVID-19 8 in patients with lung cancer: evidence and challenges COVID-19 prevalence and mortality in patients with 11 cancer and the effect of primary tumour subtype and patient demographics: a prospective 12 cohort study. The Lancet Oncology Lung cancer patients with COVID-19 in 15 Spain: GRAVID study Clinical characteristics and risk factors associated with 17 COVID-19 disease severity in patients with cancer in Wuhan, China: a multicentre, 18 retrospective, cohort study. The Lancet Oncology Clinical impact of COVID-19 on patients with 21 cancer (CCC19): a cohort study Impact of COVID-19 Infection on Patients with 24 Cancer: Experience in a Latin American Country: The ACHOCC-19 Study Lymphopenia and neutrophilia at admission predicts 27 severity and mortality in patients with COVID-19: a meta-analysis Lymphopenia in COVID-19: Therapeutic opportunities Procalcitonin to initiate or discontinue antibiotics in acute 32 respiratory tract infections Is procalcitonin-guided antimicrobial use cost-effective in adult 1 patients with suspected bacterial infection and sepsis? Prognostic Value of Serum Procalcitonin in 4 COVID-19 Patients: A Systematic Review Procalcitonin for patient stratification and identification of 7 bacterial co-infection in COVID-19 Procalcitonin for diagnosis of infection and guide to 10 antibiotic decisions: past, present and future Transcriptional response modules characterize IL-1β and 13 IL-6 activity in COVID-19. iScience Tocilizumab among patients with COVID-19 in the intensive 18 care unit: a multicentre observational study Effect of Dexamethasone on Days Alive and 21 Ventilator-Free in Patients With Moderate or Severe Acute Respiratory Distress Syndrome 22 and COVID-19: The CoDEX Randomized Clinical Trial A Trial of Lopinavir-Ritonavir in Adults Hospitalized with 25 Severe Covid-19 Remdesivir for the Treatment of Covid-19 -27 Final Report Physical distancing, face masks, and eye protection to 30 prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review 31 and meta-analysis A cross-country database of COVID-19 testing. Sci 34 Data Adapting hospital capacity to meet changing 1 demands during the COVID-19 pandemic Fifth-week immunogenicity and safety of anti-4 SARS-CoV-2 BNT162b2 vaccine in patients with multiple myeloma and myeloproliferative 5 malignancies on active treatment: preliminary data from a single institution Safety and immunogenicity of one versus two 8 doses of the COVID-19 vaccine BNT162b2 for patients with cancer: interim analysis of a 9 prospective observational study. The Lancet Oncology Association of clinical factors and recent 12 anticancer therapy with COVID-19 severity among patients with cancer: a report from the 13 COVID-19 and Cancer Consortium Abstract S12-03: Thoracic cancers 16 international COVID-19 collaboration (TERAVOLT): Small-cell lung cancer and other rare 17 thoracic malignancies Associated With COVID-19 Vaccine Hesitancy Among Patients With Breast Cancer This study was awarded a grant from the Lung Ambition that supported database development 41 and maintenance. 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