ABSTRACT
Background: Inflammation and neutrophils play a central role in severe Covid-19 disease. In previous data, we showed that the FLARE score, combining both tumor and Covid-19-induced proinflammatory status (proinflamstatus), predicts early mortality in cancer patients (pts) with Covid-19 infection. We aimed to assess the impact of this score in a larger cohort and characterize the immunophenotype (IF) of circulating neutrophils. Methods: Multicenter retrospective cohort (RC) of pts with cancer and Covid-19 infection across 14 international centers. Circulating inflammatory markers were collected at two timepoints: baseline (-15 to -45d before Covid-19 diagnosis) and Covid-19 diagnosis. Tumor-induced proinflam-status was defined by high dNLR (neutrophils/(leucocytes-neutrophils)> 3) at baseline. Covid-19-induced proinflam-status was defined by +100% increase of dNLR between both timepoints. We built the FLARE score combining both Tumor and Infection-induced inflammation: T+/I+ (poor), if both proinflam-status;T+/I- (T-only), if inflammation only due to tumor;T-/I+ (I-only), if inflammation only due to Covid;T-/I- (favorable), if no proinflam-status. The IF of circulating neutrophils by flow cytometry was determined in a unicenter prospective cohort (PC) of pts with cancer during Covid-19 infection and in healthy volunteers (HV). Primary endpoint was 30-day mortality. Results: 524 pts were enrolled in the RC with a median follow- up of 84d (95%CI 78-90). Median age was 69 (range 35-98), 52% were male and 78% had baseline PS <1.Thoracic cancers were the most common (26%). 70% had active disease, 51% advanced stage and 57% were under systemic therapy. dNLR was high in 25% at baseline vs 55% at Covid-19 diagnosis. The median dNLR increase between both timepoints was +70% (IQR: 0-349%);42% had +100% increase of dNLR. Pts distribution and mortality across FLARE groups is resumed in the Table. Overall mortality rate was 26%. In multivariate analysis, including gender, stage and PS, the FLARE poor group was independently associated with 30-day mortality [OR 5.27;1.37-20.3]. 44 pts were enrolled in the PC. Median circulating neutrophils were higher in pts with cancer (n=10, 56.7% [IQR: 39-78.4%]) vs HV (n=6, 35.8% [IQR: 25.6-21%]), and particularly higher in pts with cancer and severe Covid-19 infection (n=7, 88.6% [IQR: 80.9-94%] (p=0.003). A more comprehensive characterization of the IF of circulating neutrophils, including Lox1/CD62/CD64, will be presented at ASCO. Conclusions: The FLARE score, combining tumor and Covid-19-induced proinflam-status, can identify the population at higher risk for mortality. A better characterization of circulating neutrophils may help improve the prediction of Covid-19 outcomes in pts with cancer. (Table Presented).
ABSTRACT
Background: COVID-19 pandemic has drastically changed the management of patients with cancer;however, limited data exists regarding which pre-conditions affect the course of COVID-19 infection. Here, we sought to assess the clinical features and outcomes of COVID-19 infection in a large cohort of patients with cancer. Methods: We conducted a multicenter retrospective cohort study of patients with cancer diagnosed with SARS-CoV-2 infection by RT-PCR/Ag detection (n=274) or CT-scan (N=13) between 7/March and 30/April across 12 international centers. Clinical, pathological and biological data were collected. Primary endpoints were 30-day mortality rate and the rate of severe acute respiratory failure (SARF), defined by oxygen requirements >15 L/min. Descriptive statistics were used. Results: 287 patients were enrolled with a median follow-up of 23 days [95%CI 22-26]. Median age was 69 (range 35-98), 52% were male, 49% had hypertension and 23% had cardiovascular disease. As per cancer characteristics, 68% had active disease, 52% advanced stage and 79% had a baseline ECOG PS ≤1. Most frequent cancer-types were: 26% thoracic, 21% gastrointestinal, 19% breast and 15% genitourinary. Most patients (61%) were under systemic therapy, including chemotherapy (51%), endocrine therapy (23%) and immunotherapy (19%). At COVID-19 diagnosis, 44% of patients had moderate/severe symptoms such as fever (70%), cough (54%) and dyspnea (48%). The majority of patients (90%) required in-patient management and the median hospital stay duration was 10 days (range 1-52);8% of patients required intermediate or intensive care unit admission. Patients received treatment with: hydroxychloroquine (81%), azithromycin (61%), antiviral therapy (38%) and immunomodulatory drugs (14%). Finally, the overall mortality rate was 27% and the rate of SARF was 26%. In patients admitted to intermediate/intensive care units, the mortality and SARF rates were 45% and 73%, respectively. Mortality rate according to ECOG PS before COVID-19 was 20% in PS≤1 and 51% in PS>2 (p<0.0001). Conclusions: Patients with cancer are a susceptible population with a high likelihood of severe complications and high mortality from COVID-19 infection. Final results and treatment outcomes will be presented at the ESMO Congress. Legal entity responsible for the study: Aleix Prat. Funding: Has not received any funding. Disclosure: E. Auclin: Travel/Accommodation/Expenses: Mundipharma;Speaker Bureau/Expert testimony: Sanofi Genzymes. S. Pilotto: Speaker Bureau/Expert testimony: Astra-Zeneca;Eli-Lilly;BMS;Boehringer Ingelheim;MSD;Roche. L. Mezquita: Speaker Bureau/Expert testimony, Research grant/Funding (self), Travel/Accommodation/Expenses: Bristol-Myers Squibb;Speaker Bureau/Expert testimony: Tecnofarma;Speaker Bureau/Expert testimony, Non-remunerated activity/ies: AstraZeneca;Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche;Research grant/Funding (self): Boehringer Ingelheim. A. Prat: Honoraria (institution), Speaker Bureau/Expert testimony: Roche;Daiichi Sankyo;Honoraria (institution), Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer;Novartis;Amgen;Speaker Bureau/Expert testimony: BMS;Advisory/Consultancy: Puma;Oncolytics Biotech;MSD;Honoraria (institution), Advisory/Consultancy: Lilly;Honoraria (institution), Speaker Bureau/Expert testimony: Nanostring technologies;Officer/Board of Directors: Breast International Group;Officer/Board of Directors: Solti's Foundation;Leadership role: Actitud Frente al Cancer Foundation;Honoraria (institution): Boehringer;Honoraria (institution): Sysmex Europa GmbH;Honoraria (institution): Medica Scientia inno. Research;Honoraria (institution): Celgene;Honoraria (institution): Astellas Pharma. All other authors have declared no conflicts of interest.
ABSTRACT
Background: Inflammation plays a central role in severe COVID-19 disease. Likewise, in cancer patients (pts), a circulating pro-inflammatory status (proinflam-status) is associated with poor outcomes. We aimed to assess if a proinflam-status induced by cancer can negatively impact on COVID-19 outcomes. Methods: Multicenter retrospective cohort of cancer pts with SARS-CoV-2 infection across 12 international centers. Circulating inflammatory markers were collected at two timepoints: pre-COVID condition (-15 to -45d before COVID-19 diagnosis) and COVID-19 diagnosis. Tumor-induced proinflam-status was defined by high derived neutrophil to lymphocyte ratio (dNLR>3) at pre-COVID condition. COVID-induced proinflam-status was defined by +100% increase of dNLR between both timepoints. We built the FLARE score, combining both Tumor and Infection-induced inflammation: T+/I+ (poor), if both proinflam-status;T+/I- (T-only), if inflammation only due to tumor;T-/I+ (I-only), if inflammation only due to COVID;and T-/I- (favorable), if no inflam-status. Primary endpoint was 30-day mortality. Results: 287 pts were enrolled with a median follow-up of 23d [95%CI 22-26]. Median age was 69 (range 35-98), 52% were male and 49% had hypertension. As per cancer characteristics: 68% had active disease, 52% advanced stage and 79% had a baseline PS≤1. Thoracic cancers were the most common (26%) and 61% of pts were under systemic therapy. The dNLR was high in 24% at pre-COVID condition vs. 55% at COVID-19 diagnosis. Median change between both timepoints was +67% (IQR: 0% to +153%);40% had +100% increase of dNLR. Pts distribution across FLARE groups were: 5% in poor (n=9), 20% in T-only (n=39), 35% in I-only (n=69) and 40% in favorable (n=80). Overall mortality rate was 27%. According to FLARE score: 67% mortality for poor vs. 35% for I-only vs. 33% for T-only vs. 19% in favorable group (p=0.008). The FLARE poor group was independently associated with 30-day mortality [OR 5.7;1.02-31.2]. Conclusions: Both tumor and infection-induced proinflam-status impact on COVID-19 outcomes in cancer pts. The FLARE score, based on simple dynamics between two timepoints, allows to identify the population at higher risk for early death. Legal entity responsible for the study: Aleix Prat. Funding: Has not received any funding. Disclosure: E. Auclin: Travel/Accommodation/Expenses: Mundipharma;Speaker Bureau/Expert testimony: Sanofi Genzymes. S. Pilotto: Speaker Bureau/Expert testimony: AstraZeneca;Eli-Lilly;BMS;Boehringer Ingelheim;MSD;Roche. A. Prat: Honoraria (institution), Speaker Bureau/Expert testimony: Roche;Honoraria (institution), Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer;Novartis;Amgen;Speaker Bureau/Expert testimony: BMS;Honoraria (institution), Speaker Bureau/Expert testimony: Daiichi Sankyo;Nanostring technologies;Advisory/Consultancy: Puma;Oncolytics Biotech;MSD;Honoraria (institution), Advisory/Consultancy: Lilly;Honoraria (institution): Boehringer;Sysmex Europa GmbH;Medica Scientia inno. Research;Celgene;Astellas Pharma;Officer/Board of Directors: Breast International Group;Solti's Foundation;Leadership role: Actitud Frente al Cancer Foundation. L. Mezquita: Speaker Bureau/Expert testimony, Research grant/Funding (self), Travel/Accommodation/Expenses: Bristol-Myers Squibb;Speaker Bureau/Expert testimony: Tecnofarma;Speaker Bureau/Expert testimony, Non-remunerated activity/ies: AstraZeneca;Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche;Research grant/Funding (self): Boehringer Ingelheim. All other authors have declared no conflicts of interest.
ABSTRACT
Background: Smoking is the leading cause of cancer worldwide. Active smoking alters the inflammatory environment of the respiratory epithelium, increasing the production of potent pro-inflammatory cytokines that promote the recruitment of macrophages and neutrophils, leading to lung damage. We hypothesize that smoking-induced inflammation can impact on COVID-19 infection severity and mortality related to the proinflammatory cascade. Methods: Multicenter retrospective cohort of cancer patients (pts) with COVID-19 infection diagnosed by PCR/Ag detection (n=274) and CT-scan (N=13) in Mar-Apr/20r in 12 centers. Clinical and biological data were collected. Smoker was defined as active tobacco consumption and heavy smoker as >30 pack-year (PY). Primary endpoints were 30-day mortality rate and the rate of severe acute respiratory failure (SARF), defined by oxygen requirements >15 L/min. Results: A total of 287 pts were enrolled: 25 (9%) were active smokers, 127 (47%) were former and 116 (43%) never smoker. Among active smokers: 73% were heavy smokers, median age was 62y, 60% were male and median body mass index was 22. Regarding their comorbidities: 25% had hypertension, 8% cardiovascular disease, 28% chronic obstructive pulmonary disease and 24% diabetes. Thoracic tumors were the most common (52%), 72% had advanced disease and 56% were under systemic therapy. 92% of active smokers required hospitalization, 68% developed pneumonia and 58% required oxygen. Only 4% were escalated to the intensive care unit. Active smokers received treatment with hydroxychloroquine (91%), azithromycin (61%), antiviral therapy (33%) and steroids (29%). Only 4% received immunomodulatory drugs. SARF was the most common complication (25%) and no thromboembolic events were observed. A pro-inflammatory status was observed at COVID-19 diagnosis in active smokers, e.g. median of absolute neutrophil count was 6.35 (vs. 5.4), mean ferritin was 1269 (vs. 991) and D-Dimer was 2422 (vs. 1816);but with no significant differences. Overall mortality rate was 27%. Mortality rate was higher in active smokers (40% vs. 24% in non-smokers;p=0.08). Conclusions: Active smoking might be associated with severe COVID-19 infection and early death in cancer patients. Smoking induced-inflammation should be further explored. Legal entity responsible for the study: Aleix Prat. Funding: Has not received any funding. Disclosure: E. Auclin: Travel/Accommodation/Expenses: Mundifarma;Speaker Bureau/Expert testimony: Sanofi Genzime. S. Pilotto: Speaker Bureau/Expert testimony: Astra-Zeneca;Speaker Bureau/Expert testimony: Boehringer Ingelheim;Speaker Bureau/Expert testimony: Eli-Lilly;Speaker Bureau/Expert testimony: BMS. A. Prat: Honoraria (institution), Speaker Bureau/Expert testimony: Roche;Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer;Honoraria (institution), Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis;Amgen;Speaker Bureau/Expert testimony: BMS;Honoraria (institution), Speaker Bureau/Expert testimony: Daiichi Sankyo;Nanostring;Advisory/Consultancy: Puma;Oncolytics Biotech;MSD;Honoraria (institution), Advisory/Consultancy: Lilly;Boehringer;Sysmex Europa GmbH;Medican Scientia inno. Research;Celgene;Astellas;Officer/Board of Directors: Breast International Group;Solti's Foundation;Actitud frente al cancer foundation. L. Mezquita: Speaker Bureau/Expert testimony, Research grant/Funding (self), Travel/Accommodation/Expenses: Bristol-Meyers Squibb;Speaker Bureau/Expert testimony: Tecnofarma;Honoraria (institution), Speaker Bureau/Expert testimony: Astrazeneca;Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche;Research grant/Funding (self): Boehringer Intelligence. All other authors have declared no conflicts of interest.
ABSTRACT
Background: Cancer patients (pts) have been associated with severe SARS-CoV2 infection and higher mortality compared with the general population. This could be related to the limitation of therapeutic effort based on their prognosis and healthcare prioritization towards non-cancer pts. The oncologist’s role could be crucial for providing high-quality care. We aim to assess the impact of oncologists (ONC) on COVID-19 management. Methods: Multicentre retrospective analysis of cancer pts diagnosed with COVID-19 between Mar-Apr 2020. We classified pts according to an estimated life expectancy (based on tumor/stage/line) in 3 groups: favourable group (FG) mOS >5 years (y), intermediate (IG) 1-5y and poor (PG) <1y. We studied COVID-19 management based on oncologist’s involvement: mainly-ONC vs. mainly other specialists (Other). Primary endpoint: COVID-19 30-day mortality (early-M). Secondary outcomes: intensive care unit admission (ICUa), the incidence of acute respiratory distress syndrome (ARDS) and antiretroviral treatment (ARVt) and immunomodulatory drugs (ImD) administered. Results: 287 pts were enrolled, median age 69 (35-98), 52% male, 67% with an active tumor (of them 76% had advanced stage). Mostly thoracic tumors (26%), followed by gastrointestinal (21%) and breast (19%). Among 170 pts under treatment, 89 (52%) received chemotherapy (CHT). By prognostic group: 49% were included in FG (n=135), 40% in IG (n=113), and 11% in PG (n=30). Overall early-M rate was 27% (ONC 22% vs. Other 27%). Prognostic groups were associated with early-M: 19% (FG) vs. 31% (IG) vs. 37% (PG) (p=0.022). No significant differences regarding rate of ARDS (23% FG vs. 19% IG vs. 17% PG). The ONC-group (n=18) included 4 PG and 14 IG, 94% had an advanced stage disease, 83% receive CHT and 65% had PS≥2 (p=0.05 compared to Other group). In IG (ONC vs. Other): 7% vs. 2% ICUa, 100% vs. 34% ARVt and 57% vs. 7% ImD (all p<0.001). In PG (ONC vs. Other): 25% vs. 0% ICUa, 75% vs. 34% ARVt and 25% vs. 0% ImD (all p<0.001). Finally, FP managed only by Other: 13% ICUa;33% ARVt and 13% ImD. Conclusions: Oncologist mostly treated complex pts compared to other specialists. During COVID-19 crisis, setting prognostic groups helped to individualized therapeutic approaches, reflected by less mortality rate and no differences in terms of complications. Legal entity responsible for the study: Aleix Prat. Funding: Has not received any funding. Disclosure: L. Ghiglione: Licensing/Royalties: Hibor;Licensing/Royalties: Kyowa Kirin;Licensing/Royalties: Vifor Pharma. E. Auclin: Travel/Accommodation/Expenses: Mundipharma;Licensing/Royalties: Sanofi Genzymes. S. Pilotto: Licensing/Royalties: AstraZeneca;Eli-Lilly;BMS;: Boehringer Ingelheim;MSD;Roche. A. Prat: Research grant/Funding (institution), Licensing/Royalties: Roche;Advisory/Consultancy, Research grant/Funding (institution), Licensing/Royalties: Pfizer;Novartis;Amgen;Licensing/Royalties: BMS;Research grant/Funding (institution), Licensing/Royalties: Daiichi Sankyo;Advisory/Consultancy: Puma;Oncolytics Biotech;MSD;Advisory/Consultancy, Research grant/Funding (institution): Lilly;Research grant/Funding (institution), Licensing/Royalties: Nanostring technologies;Officer/Board of Directors: Beast International Group (BIG);Solti's Foundation;Actitud frente al cancer Foundation;Solti;Research grant/Funding (institution): Boehringer;Sysmex Europa GmbH;Medica Scientia inno. Research, SL;Celgene, SLU;Astellas Pharma. L. Mezquita: Research grant/Funding (self), Travel/Accommodation/Expenses, Licensing/Royalties: Bristol-Myers Squibb;Licensing/Royalties: Tecnofarma;Licensing/Royalties, International Mentorship Program: AstraZeneca;Advisory/Consultancy, Travel/Accommodation/Expenses, Licensing/Royalties: Roche;Advisory/Consultancy: Roche Diagnostics;Research grant/Funding (self): Boehringer Ingelheim. All other authors have declared no conflicts of interest.