Epidemiology and clinical course of SARS-CoV-2 infection in cancer patients in the Veneto Oncology Network during the first and second pandemic waves.
Authors: Valentina Guarneri, Mario Caccese, Giuseppe Azzarello, Franco Bassan, Vanna Chiarion-Sileni, Rita Chiari, Adolfo G. Favaretto, Marta Zaninelli, Alberto Pavan, Vittorina Zagonel, Davide Pastorelli, Anna Roma, Cristina Oliani, ARIANNA FUMAGALLI, Daniele Bernardi, Stefania Gori, Michele Celestino, Maria Vittoria Dieci, Pierfranco Conte
Journal: Journal of Clinical Oncology (2021)

6511 Background: Since the beginning of the COVID-19 outbreak, the Veneto Oncology Network ROV licensed dedicated guidelines for cancer patients care during the pandemic, and developed a regional registry (ROVID) aimed at describing epidemiology and clinical course of SARS-CoV-2 infection in cancer patients. Preliminary data on 170 patients mainly diagnosed during the first pandemic wave have been published (Guarneri V, Eur J Cancer 2021). Here we report the data of additional 270 patients, comparing clinical data and outcomes between first (W1) and second (W2) pandemic waves. Methods: All patients with cancer diagnosis and documented SARS-CoV-2 infection are eligible. Data on diagnosis, comorbidities, anticancer treatments, details on SARS-CoV-infection including source of contagion, clinical presentation, hospitalization, treatments and fate of the infection are recorded. Results: 440 patients have been enrolled, 196 diagnosed during W1 (until September 2020) and 244 during W2. The most common cancer type was breast cancer (n = 116). Significant differences in clinical characteristics between W1 and W2 were the followings: ECOG PS 0 (34% vs 58%), presence of cardiac comorbidities (30% vs 13%), presence of any co-morbidities (81% vs 62%), smoking habits (23% vs 13%). Patients diagnosed in W1 were less likely on active anticancer therapy (54% vs 73%) at the time of SARS-CoV-2 infection. Distribution per stage, presence of lung metastases, disease setting (curative vs palliative), active treatment discontinuation due to infection were similar between W1 and W2. Patients diagnosed in W1 were more likely symptomatic for SARS-CoV-2 infection (80% vs 67%), and reported more frequently an in-hospital contact as potential source of infection (44% vs 9%). Significantly more patients diagnosed in W1 were hospitalized (76% vs 25%). All-cause mortality rates were 30.6% for patients diagnosed in W1 vs 12% for patients diagnosed in W2 (p &lt; 0.001). However, deaths due to SARS-CoV-2 infection were more frequent in patients diagnosed in W2 (86% vs 54%, odds ratio 3.22; 95% CI 1.97-5.279). Conclusions: Differences in clinical characteristics between W1 and W2 reflect different pattern of virus circulation. The dramatic reduction of in-hospital contact as a source of infection reflects the efforts put in place to protect this vulnerable population from in-hospital exposure. The lower all-cause mortality rate observed in W2 is in line with the observed less frail population. However, the higher relative risk of death due to SARS-CoV-2 infection observed in W2 reinforces the need to adopt protective measures including vaccination in cancer patients, irrespectively of age, stage, and comorbidities.