ABSTRACT
Background: In first line (L1) for EGFR-mutated (mEGFR) advanced NSCLC (aNSCLC), osimertinib (osi) has been the preferred option since 2018. First generation anti-EGFR TKI (1G) alone followed by osi, or 1G + anti-angiogenic or 1G + chemotherapy are other options. We aimed to assess the subgroups of patients (pts) that do not benefit from 1G alone compared with osimertinib L1 in mEGFR aNSCLC. Methods: Retrospective international study including pts with mEGFR aNSCLC treated with either osi or the sequence of 1G followed by osi (seq group). Primary endpoint was the PFS of the global strategy (PFSglob) defined as the time between L1 start and progression after L2 treatment or death. Subgroups analyses included pts with high tumour burden (high-TM;> 3 metastatic sites and/or central nervous system (CNS) involvement), poor performance status (PS), and T790M negative (seq subgroup only). Results: A total of 235 pts were included: 104 in the seq group, 118 in the osi L1 group. 15 had T790M negative at PD after 1G, they received osi as a therapeutic test. From these pts, 222 had an exon19 or 21 EGFR mut, 13 had uncommon mEGFR. Mean age was 65 years, 64% were female, and 60% never smokers. Pts from the osi L1 group had poorer PS (23% vs 10%), higher rate of co-mutations (23% vs 19%) and more CNS involvement (47% vs 19%). After a median (m) follow up of 30.6 months in the exon 19 and 21 population, mPFSglob was 27.4 mo (23.0-31.0) and mPFS L1 was 15.5mo (13.7-18.4) Table. The sequence was associated with shorter PFS L1 compared with osi L1 particularly in high-TM (10.5 mo vs 17.1 mo, p<0.0001);PFS was numerically shorter in poor PS (≥2) population (11.0 mo vs 15.6 mo, p=0.1). [Formula presented] Conclusions: 1G TKI followed by osi seemed to be detrimental compared with os L1 for pts with high-TM or poor PS mEGFR aNSCLC. In this population, the intensification of L1 treatment with osimertinib or a combination of 1G with anti-angiogenic or chemotherapy could be the better option in the first-line setting. Updated results will be presented at the congress. Legal entity responsible for the study: Institut Gustave Roussy. Funding: Has not received any funding Disclosure: E. Auclin: Financial Interests, Personal, Advisory Board: Sanofi, Amgen. N. Girard: Financial Interests, Personal, Invited Speaker: AstraZeneca, BMS, MSD, Roche, Pfizer, Mirati, Amgen, Novartis, Sanofi;Financial Interests, Personal, Advisory Board: AstraZeneca, BMS, MSD, Roche, Pfizer, Janssen, Boehringer, Novartis, Sanofi, AbbVie, Amgen, Lilly, Grunenthal, Takeda, Owkin;Financial Interests, Institutional, Research Grant, Local: Roche, Sivan, Janssen;Financial Interests, Institutional, Funding: BMS;Non-Financial Interests, Officer, International Thymic malignancy interest group, president: ITMIG;Other, Other, Family member is an employee: AstraZeneca. M.T. Moran Bueno: Financial Interests, Personal, Advisory Board, Advisory Role: AstraZeneca, Boehringer Ingelheim, BMS;Financial Interests, Personal, Advisory Board, Advisory role: Roche. B. Besse: Financial Interests, Institutional, Funding: 4D Pharma, AbbVie, Amgen, Aptitude Health, AstraZeneca, BeiGene, Blueprint Medicines, Boehringer Ingelheim, Celgene, Cergentis, Cristal Therapeutics, Daiichi Sankyo, Eli Lilly, GSK, Janssen, Onxeo, Ose Immunotherapeutics, Pfizer, Roche-Genentech, Sanofi, Takeda, Tolero Pharmaceuticals;Financial Interests, Institutional, Research Grant: Chugai Pharmaceutical, EISAI, Genzyme Corporation, Inivata, Ipsen, Turning Point Therapeutics. L. Mezquita: Financial Interests, Personal, Advisory Board: Takeda, AstraZeneca, Roche;Financial Interests, Personal, Invited Speaker: Roche, BMS, AstraZeneca, Takeda;Financial Interests, Personal, Research Grant, SEOM Beca Retorno 2019: BI;Financial Interests, Personal, Research Grant, ESMO TR Research Fellowship 2019: BMS;Financial Interests, Institutional, Research Grant, COVID research Grant: Amgen;Financial Interests, Institutional, Invited Speaker: Inivata, Stilla. All other authors have declared no conflicts of interest.
ABSTRACT
Background: The value of increased HER2 gene copy number (GCN) in NSCLC is unclear. In this study we defined its frequency and characterized a cohort of patients harboring it. Methods: Patients with stage IIIB/IV NSCLC enrolled in the Gustave Roussy MSN study (NCT02105168) between Oct. 2009 and Feb. 2016 were screened by FISH (positivity defined as HER2 GCN to centromeres ratio ≥ 2) and tested for other molecular alterations. Descriptive analyses of clinical-pathological data were performed, progression-free survival (PFS) and overall survival (OS) were estimated by Kaplan-Meier method. Results: HER2 FISH tested positive in 22 of 250 screened patients (9%). Median age was 60 years (range 47-80), 68% (n=15) were male, 91% (n=20) were current or former tobacco smokers (median exposure 47 pack-year), 64% (n=14) had adenocarcinoma, 18% (n=4) squamous cell and 18% (n=4) large cell carcinoma. 91% (n=20) had an ECOG PS of 0 or 1. Stage IV with extra-thoracic involvement was the most common clinical presentation (64%, n=14). Overall, 95% of patients (n=21) had 1 or 2 metastatic sites at diagnosis (bone 32%, lung 27%, nodes 18%, liver 18%, brain 18%). In 9 patients (41%) 12 concurrent molecular alterations were detected: 5 KRAS mutation (3 G12C, 1 G12D, 1 G61H), 2 HER2 exon 20 insertion, 1 EGFR exon 19 deletion, 1 BRAF V600E mutation, 1 ALK rearrangement, 1 FGFR1 and 1 MET amplification. 18 patients received first-line platinum-based chemotherapy, with 33% (95% CI 16-56) objective response rate and 83% (95% CI 61-94) disease control rate. After a median follow-up of 28 months (95% CI 23-45), median PFS and OS were 5.9 (95% CI 3.4-11.0) and 15.3 (95% CI 10.3-NR) months, respectively. Median PFS was longer in patients with higher GCN. As further line of treatment, 5 patients received trastuzumab: 4 in combination with chemotherapy and 1 as monotherapy, with 1 stabilization of disease as best response. 3 patients received nivolumab (1 partial response and 1 stable disease) and 3 a targeted therapy (anti ALK, EGFR, BRAF). Conclusions: Increased HER2 GCN was found in 9% of patients with unresectable NSCLC, was not correlated to particular clinical characteristics, but frequently occurred with other molecular alterations. Its clinical actionability and the correlation with protein expression deserve further characterization. Clinical trial identification: NCT02105168. Legal entity responsible for the study: Gustave Roussy. Funding: Has not received any funding. Disclosure: M. Tagliamento: Other, Personal, Other, Travel grants: Roche, Bristol-Myers Squibb, AstraZeneca, Takeda, Eli Lilly;Other, Personal, Writing Engagements, Honoraria as medical writer: Novartis, Amgen. E. Auclin: Financial Interests, Personal, Advisory Board: Amgen, Sanofi. E. Rouleau: Financial Interests, Institutional, Advisory Board: AstraZeneca, Roche, Amgen, GSK;Financial Interests, Institutional, Invited Speaker: Clovis, BMS;Financial Interests, Institutional, Funding, Data base: AstraZeneca. A. Bayle: Non-Financial Interests, Institutional, Other, Principal/Sub-Investigator of Clinical Trials: AbbVie, Adaptimmune, Adlai Nortye USA Inc, Aduro Biotech, Agios Pharmaceuticals, Amgen, Argen-X Bvba, Astex Pharmaceuticals, AstraZeneca Ab, Aveo, Basilea Pharmaceutica International Ltd, Bayer Healthcare Ag, Bbb Technologies Bv, BeiGene, BicycleTx Ltd, Non-Financial Interests, Institutional, Research Grant: AstraZeneca, BMS, Boehringer Ingelheim, GSK, INCA, Janssen Cilag, Merck, Novartis, Pfizer, Roche, Sanofi;Financial Interests, Institutional, Other, drug supplied: AstraZeneca, Bayer, BMS, Boehringer Ingelheim, GSK, MedImmune, Merck, NH TherAGuiX, Pfizer, Roche. F. Barlesi: Financial Interests, Personal, Advisory Board: AstraZeneca, Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Eli Lilly Oncology, F. Hoffmann–La Roche Ltd, Novartis, Merck, Mirati, MSD, Pierre Fabre, Pfizer, Sanofi-Aventis, Seattle Genetics, Takeda;Non-Financial Interests, Principal Investigator: AstraZeneca, BMS, Merck, Pierre Fabre, F. Hoffmann-La Roche Ltd. D. Planchard: Financial I terests, Personal, Advisory Board: AstraZeneca, BMS, Merck, Novartis, Pfizer, Roche, Samsung, Celgene, AbbVie, Daiichi Sankyo, Janssen;Financial Interests, Personal, Invited Speaker: AstraZeneca, Novartis, Pfizer, priME Oncology, Peer CME, Samsung, AbbVie, Janssen;Non-Financial Interests, Principal Investigator, Institutional financial interests: AstraZeneca, BMS, Merck, Novartis, Pfizer, Roche, Daiichi Sankyo, Sanofi-Aventis, Pierre Fabre;Non-Financial Interests, Principal Investigator: AbbVie, Sanofi, Janssen. B. Besse: Financial Interests, Institutional, Funding: 4D Pharma, AbbVie, Amgen, Aptitude Health, AstraZeneca, BeiGene, Blueprint Medicines, Boehringer Ingelheim, Celgene, Cergentis, Cristal Therapeutics, Daiichi Sankyo, Eli Lilly, GSK, Janssen, Onxeo, Ose Immunotherapeutics, Pfizer, Roche-Genentech, Sanofi, Takeda, Tolero Pharmaceuticals;Financial Interests, Institutional, Research Grant: Chugai Pharmaceutical, EISAI, Genzyme Corporation, Inivata, Ipsen, Turning Point Therapeutics. L. Mezquita: Financial Interests, Personal, Advisory Board: Takeda, AstraZeneca, Roche;Financial Interests, Personal, Invited Speaker: Roche, BMS, AstraZeneca, Takeda;Financial Interests, Personal, Research Grant, SEOM Beca Retorno 2019: BI;Financial Interests, Personal, Research Grant, ESMO TR Research Fellowship 2019: BMS;Financial Interests, Institutional, Research Grant, COVID research Grant: Amgen;Financial Interests, Institutional, Invited Speaker: Inivata, Stilla. All other authors have declared no conflicts of interest.
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: Lower risk of COVID-19 was reported in men with prostate cancer receiving androgen deprivation therapy while low levels of testosterone (T) were associated with a more severe disease and poor clinical outcomes in COVID-19 male patients (pts). In the latter case, it is unclear whether low levels of T and dihydrotestoserone (DHT) are risk factors or consequences of COVID-19. Here, we investigated T and DHT levels impact on COVID-19 severity in ambispective cohorts of symptomatic SARS-CoV-2 infected males. Methods: Both prospective (European Hospital Georges Pompidou patients, P-cohort) and retrospective (French COVID-19 cohort, REacting project, R-cohort) cohorts included male pts admitted for severe COVID-19. The P-cohort included pts admitted in a medical unit (non-ICU) or in ICU immediately (ICU-I). The R-cohort included pts admitted to a medical unit, ICU-I or to ICU secondarily (ICU-S). The size of ICU-S pts group in P-cohort was insufficient to include their data in the analysis. We collected information on pts demographics and COVID-19-related outcomes. T, DHT levels and inflammation markers were measured. Wilcoxon-Mann-Whitney test and chi2-test (or Fisher’s exact test, if appropriate) were performed. All tests were two-sided at 0.05 significance level. Results: The P-cohort included 71 pts (median age: 64 years) and the R-cohort 89 pts (median age: 62 years). The median duration between admission and measurement of hormone levels was 2 days (range: 0-16) and 0.5 days (range: 0-11) respectively. T and DHT levels were low in all pts as compared to standards and even lower in ICU pts (Table). In the R-cohort, T and DHT lowest values were observed for ICU-I pts and median values for ICU-S pts. [Formula presented] Conclusions: Low T and DHT levels were associated with the severity of the disease and the poorest clinical outcomes in males with severe COVID-19. This suggests that COVID-19 may cause a rapid and profound decrease in androgens levels and that T and DHT serum levels may be used as prognostic markers. Legal entity responsible for the study: Pr. Stéphane Oudard. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.
ABSTRACT
Introduction: COVID-19 pandemic has drastically changed the management of patients with cancer. The prioritization of the healthcare towards COVID-19 patients could interfere with the initial diagnosis, resulting in delayed treatment and worse outcome. We aimed to study the incidence of lung cancer new diagnosis, severity and clinical outcomes during Covid-19-period (during-COVID) compared to the same period in 2019 (before-COVID). Methods: Bicenter retrospective cohort study of newly diagnosed non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) patients before (Jan-Jun/19) and during COVID-19 (Jan-Jun/20) in Spain. Clinical data were collected. We primarily assessed the difference on new lung cancer cases between both periods, and the disease severity considering: Performance status (PS), stage and any significant complication at diagnosis. Secondarily, we assessed the 30 days-mortality rate, progression-free survival (PFS) and overall survival (OS) by period. Results: 162 newly diagnosed lung cancer patients (68% NSCLC and 32% SCLC) were enrolled, with median age of 66 years, 70% were male, 33% smokers, 25% with PS ≥2. Advanced disease was diagnosed in 50% of NSCLC and 61% SCLC;13% of NSCLC harbored driver alterations. During-COVID, the number of new cases diagnosed decreased by 38% (43 NSCLC;19 SCLC), compared to before-COVID period (67 NSCLC;33 SCLC). More symptomatic cases were new diagnosed during vs. before-COVID. The Table 1 summarized clinical data and complications of new lung cancer cases by period and histology. In NSCLC population diagnosed during-COVID, we observed more respiratory symptoms at diagnosis (30% vs. 23% before-COVID) with mainly locally-advanced/advanced disease (82% vs. 76% before-COVID). Among the cases hospitalized, the mortality during-hospitalization was 44% (2/9) vs. 17% before-COVID. In SCLC population diagnosed during-COVID, respiratory symptoms were more common (32% vs. 24% before-COVID), but no more aggressive disease observed in terms of stage, complications and hospitalizations. Among the 4 cases hospitalized at diagnosis, none died during-hospitalization vs. 18% before-COVID (2/11). Overall, during-Covid the mOS was 6.7 months [95% CI, 5.4-not reached] vs. 7.9 months [95% CI, 4.7-12] before-COVID. In NSCLC, the 30-days mortality was 49% vs. 25% before-COVID;in SCLC, it was 32% vs. 18% before-COVID. Updated data and treatment outcomes will be presented in the meeting. [Formula presented] Conclusion: Lung cancer diagnosis has been affected during the COVID-19 pandemic with fewer cases diagnosed and more symptomatic disease compared to 2019, which seems to be associated with worse outcomes. This study is still ongoing. Keywords: NSCLC, SCLC, COVID-19
ABSTRACT
Introduction: Covid-19 pandemic has drastically changed the management of patients with cancer;however, there is still limited data regarding the real impact of Covid-19 on patient’s outcomes due to delayed diagnosis and treatment of clinical complications. We aimed to assess the prevalence, severity and mortality of clinical complications and oncology emergencies in hospitalized patients in our institution during the Covid19 period vs. the same period of 2019. Methods: We conducted a retrospective study of patients with small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) who were admitted to the Department of Medical Oncology during Jan-Jun 2019 (before-Covid) and Jan-Jun 2020 (Covid-19 period). Clinical, pathological and biological data were collected. We assessed the clinical severity in both periods including: PS at admission, progression disease (PD), oncologic emergencies (%), start of a systemic therapy or switch to other therapy line. We also analyzed the differences on the 30-day mortality rate since hospitalization between both periods. Results: 229 admissions, 133 during and 93 before Covid-19 pandemic (N=180 patients) were enrolled;the median duration of the hospitalization was 9 days (4-16). Median age was 66 years, 35% were female, 88% with PS≥2, 27% were current smokers;83% had NSCLC histology. Most of them (82%) had advanced disease at admission;69% were under systemic therapy (chemotherapy 39%, immunotherapy 17%, targeted therapies 11%). Nine patients (4%) were active covid-19 cases (9 NSCLC, 0 SCLC). The table 1 summarized the most common clinical conditions by histology, in both periods. In NSCLC population, during-Covid, lower rate of admissions were observed (4 cases less per month), with no increase of oncologic emergencies. The PD during hospitalization was slightly higher during vs. before-Covid, but no differences were observed in 30-days mortality rate. In SCLC population, during-Covid, the rate of admissions was doubled (2 cases more per month), with more cases progressing during the hospitalization. (46% during vs. 34% before-Covid). In contrast to NSCLC, the 30-days mortality rate was higher during-Covid (38%) vs. before-Covid (20%). Updated data will be presented in the meeting. [Formula presented] Conclusion: We preliminary observed more aggressive disease with worse outcomes in patients with SCLC hospitalized during-Covid compared to the same period in 2019. No differences were observed in NSCLC. The final outcomes will be assessed in a larger and mature cohort still ongoing. Keywords: lung cancer, COVID-19, hospitalization
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.