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Background: As management and prevention strategies against Coronavirus Disease-19 (COVID-19) evolve, it is still uncertain whether prior exposure to immune checkpoint inhibitors (ICIs) affects COVID-19 severity in patients (pts) with cancer. Method(s): In a joint analysis of ICI recipients from OnCovid (NCT04393974) and ESMO CoCARE registries, we assessed severity and mortality from SARS-CoV-2 in vaccinated and unvaccinated pts with cancer and explored whether prior immune-related adverse events (irAEs) influenced outcome from COVID-19. Result(s): The study population consisted of 240 pts diagnosed with COVID-19 between Jan 2020 and Feb 2022 exposed to ICI within 3 months prior to COVID-19 diagnosis, with a 30-day case fatality rate (CFR30) of 23.6% (95%CI: 17.8-30.7%). 42 (17.5%) were fully vaccinated prior to COVID-19 and experienced decreased CFR30 (4.8% vs 28.1%, p=0.001), hospitalization rate (27.5% vs 63.2%, p<0.001), requirement of oxygen therapy (15.8% vs 41.5%, p=0.003), COVID-19 complication rate (11.9% vs 34.6%, p=0.004), and COVID-19-specific therapy (26.3% vs 57.9%, p=0.001) compared with unvaccinated pts. IPTW-fitted multivariable analysis, following a clustered-robust correction for the data source (OnCovid vs ESMO CoCARE), confirmed that vaccinated pts experienced a decreased risk of death at 30 days (aOR 0.08, 95%CI: 0.01-0.69). 38 pts (15.8%) experienced at least 1 irAE of any grade at any time prior to COVID-19, at a median time of 3.2 months (0.13-48.7) from COVID-19 diagnosis. IrAEs occurred independently of baseline characteristics except for primary tumour (p=0.037) and were associated with a significantly decreased CFR30 (10.8% vs 26.0%, p=0.0462) additionally confirmed by the IPTW-fitted multivariable analysis (aOR: 0.47, 95%CI: 0.33-0.67). Pts who experienced irAEs also presented a higher median absolute lymphocyte count at COVID-19 (1.4 vs 0.8 109 cells/L, p=0.009). Conclusion(s): Anti-SARS-CoV-2 vaccination reduces morbidity and mortality from COVID-19 in ICI recipients. History of irAEs might identify pts with pre-existing protection from COVID-19, warranting further investigation of adaptive immune determinants of protection from SARS-CoV-2. Clinical trial identification: NCT04393974 OnCovid. Legal entity responsible for the study: Imperial College London & ESMO. Funding(s): Imperial Biomedical Research Centre ESMO. Disclosure: A. Cortellini: Financial Interests, Personal, Advisory Board: MSD, OncoC4;Financial Interests, Personal, Invited Speaker: Eisai, AstraZeneca;Financial Interests, Personal, Expert Testimony: Iqvia. D.J. Pinato: Financial Interests, Personal, Invited Speaker: ViiV Healthcare, Bayer, BMS, Roche, Eisai, Falk Foundation;Financial Interests, Personal, Advisory Board: Mina Therapuetics, Eisai, Roche, DaVolterra, AstraZeneca. All other authors have declared no conflicts of interest. Copyright © 2022 European Society for Medical Oncology
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Background: The Omicron (B.1.1.529) SARS-CoV-2 variant is highly transmissible and escapes vaccinal immunity. Evidence is lacking as to the impact of Omicron in oncological patients. Method(s): Capitalizing on OnCovid study data (NCT04393974), we analysed COVID-19 morbidity and case fatality rate at 28 days (CFR28) of unvaccinated patients across 3 phases defined following the evolution of the pandemic in Europe, according to date of COVID-19 diagnosis: "Pre-vaccination" phase (27/02/2020-30/11/2020), "Alpha- Delta variant" phase (01/12/2020-14/12/2021), "Omicron variant" phase (15/12/2021-31/01/2022). Finding(s): By the data lock of 04/02/2022, 3820 patients from 37 institutions across 6 countries were entered. Out of 3473 eligible patients, 2033 (58.6%), 1075 (30.9%) and 365 (10.5%) were diagnosed during the Pre-vaccination, Alpha-Delta and Omicron phases. In total 659 (61.3%) and 42 (11.5%) were unvaccinated in the Alpha-Delta and Omicron. Unvaccinated patients across the Omicron, Alpha-Delta and Pre-vaccination phases experienced similar CFR28 (27.5%, 28%, 29%, respectively). Following propensity score matching, 42 unvaccinated Omicron patients were matched with 122 and 121 patients from the Pre-vaccination and Alpha-Delta phases respectively, based on country of origin, sex, age, comorbidity burden, primary tumour, cancer stage and status, and the receipt of systemic anticancer therapy at COVID-19. Unvaccinated Omicron patients experienced improved COVID-19 outcomes in comparison to patients diagnosed during the Prevaccination phase. Morbidity and mortality were comparable to those of unvaccinated patients diagnosed during the Alpha-Delta phase. Interpretation(s): Despite time-dependent improvements in outcomes reported in the Omicron phase, patients with cancer remain highly vulnerable to SARS-CoV-2 in absence of vaccinal protection. This study provides unequivocal evidence in support of universal vaccination of patients with cancer as a protective measure against morbidity and mortality from COVID-19.
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Background: Immunogenicity and safety of SARS-CoV-2 vaccines have been widely investigated in patients (pts) with cancer. However, their effectiveness against Coronavirus disease 2019 (COVID-19) and the additional protective effect of a booster dose in this population are yet to be defined. Methods: Using OnCovid study data (NCT04393974), a European registry enrolling consecutive pts with cancer and COVID-19, we evaluated morbidity and 14 days case fatality rates (CFR14) from COVID-19 in pts who were unvaccinated, vaccinated (either partially/full vaccinated but not boosted) and those who had received a third dose. Analyses were restricted to pts diagnosed between 17/11/2021 (first breakthrough infection in a boosted pt) and the 31/01/2022. Pts with unknown vaccination status were excluded. Results: By the data lock of 22/02/2022, out of 3820 consecutive pts from 36 institutions, 415 pts from 3 countries (UK, Spain, Italy) were eligible for analysis. Among them, 51 (12.3%) were unvaccinated, 178 (42.9%) were vaccinated and 186 (44.8%) were boosted. Among vaccinated pts, 26 (14.6%) were partially vaccinated (1 dose). Pts with haematological malignancies had more likely received a booster dose prior to infection (25.4% vs 13.6% and 11.8%, p = 0.02). We found no other associations between vaccination status and pts' characteristics including sex, age, comorbidities, smoking history, tumour stage, tumour status and receipt of systemic anticancer therapy. Compared to unvaccinated pts, boosted and vaccinated pts achieved improved CFR14 (6.8% and 7.0% vs 22.4%, p = 0.01), COVID-19-related hospitalization rates (26.1% and 20.6% vs 41.2%, p = 0.01) and COVID-19-related complications rates (14.5% and 15.7% vs 31.4%). Using multivariable Inverse Probability of Treatment Weighting (IPTW) models adjusted for sex, comorbidities, tumour status and country of origin we confirmed that boosted (OR 0.21, 95%CI: 0.05-0.89) and vaccinated pts (OR 0.19, 95%CI: 0.04-0.81) achieved improved CFR14 compared to unvaccinated pts, whilst a significantly reduced risk of COVID-19 complications (OR 0.26, 95%CI: 0.07-0.93) was reported for vaccinated pts only. Conclusions: SARS-CoV-2 vaccines protect from COVID-19 morbidity and mortality in pts with cancer. Accounting for the enrichment of haematologic pts in the boosted group, the observation of comparable mortality outcomes between boosted and vaccinated pts is reassuring and suggests boosting to be associated with reduced mortality in more vulnerable subjects, despite evidence of adverse features in this group.
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Background: Whilst patients (pts) with cancer are at increased risk of adverse outcome from Coronavirus disease 2019 (COVID-19), no evidence exists as to the natural history of the SARS-CoV-2 B.1.1.529 (Omicron) variant in this population. Methods: Capitalizing on OnCovid study data (NCT04393974), a European registry that collects data on consecutive patients with cancer and COVID-19, we analysed COVID-19 morbidity and case fatality rates at 14 days (CFR14) across 3 phases defined following the evolution of the pandemic in Europe, according to date of COVID-19 diagnosis: “Pre-vaccination” phase (27/02/2020-30/ 11/2020), “Alpha-Delta variant” phase (01/12/2020-14/12/2021), “Omicron variant” phase (15/12/2020-31/01/2022). Results: By the data lock of 04/02/2022, 3820 consecutive pts were enrolled, 3473 of whom were eligible for this analysis. Among them, 2033 (58.6%), 1075 (30.9%) and 365 (10.5%) were diagnosed during the Pre-vaccination, Alpha-Delta and Omicron phases. Pts diagnosed in the Omicron phase were more likely aged < 65 years (48.6% vs 42.5%, 39.4% p = 0.01), had < 2 comorbidities (61.9% vs 55.6%, 52.1% p = 0.01). They had more advanced-stage tumours (62.1% vs 53.3%, 49.0%, p < 0.01) and were more likely receiving systemic anticancer therapy (SACT) at COVID-19 diagnosis (54.9% vs 43.9%, 39.6%, p < 0.01). Proportions of fully vaccinated/boosted pts were higher in the Omicron phase (33.9%-48.1%) compared to the Alpha-Delta phase (16.6%-2.3%, p < 0.01). Pts diagnosed in the Omicron phase had improved CFR14 (9.0% vs 13.9%, 23.1%, p < 0.01) lower hospitalization rates due to COVID-19 (24.4% vs 41.4%, 56.6%, p < 0.01), lower complications rates (15.3% vs 33.6%, 39.4%, p < 0.01) and reduced need for COVID-19 specific therapy (22.4% vs 43.0%, 65.7% p < 0.01) compared to the Alpha-Delta and pre-vaccinal phase. After adjusting for country of origin, sex, age, comorbidities, tumour stage, status and receipt of SACT at COVID-19, patients diagnosed in the Omicron phase displayed the lowest risk of death at 14 days compared to earlier phases. Similarly, rates of hospitalization and complicated COVID-19 were lowest for Omicron phase. Conclusions: This is the first study to portray the evolution of the SARS-CoV-2 Omicron outbreak in Europe, documenting an improvement in all COVID-19 outcomes compared to earlier phases of the pandemic. Enhanced healthcare capacity, improved disease management, immunization campaigns alongside differential virulence of viral strains are likely contributing to improved outcomes across phases.
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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).
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We sought to determine parameters of the acute phase response, a feature of innate immunity activated by infectious noxae and cancer, deranged by Covid-19 and establish oncological indices' prognostic potential for patients with concomitant cancer and Covid-19. Between 27/02 and 23/06/2020, OnCovid retrospectively accrued 1,318 consecutive referrals of patients with cancer and Covid-19 aged 18 from the U.K., Spain, Italy, Belgium, and Germany. Patients with myeloma, leukemia, or insufficient data were excluded. The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), prognostic nutritional index (PNI), modified Glasgow prognostic score (mGPS), and prognostic index (PI) were evaluated for their prognostic potential, with the NLR, PLR, and PNI risk stratifications dichotomized around median values and the pre-established risk categorizations from literature utilized for the mGPS and PI. 1,071 eligible patients were randomly assorted into a training set (TS, n=529) and validation set (VS, n=542) matched for age (67.9±13.3 TS, 68.5±13.5 VS), presence of 1 comorbidity (52.1% TS, 49.8% VS), development of 1 Covid-19 complication (27% TS, 25.9% VS), and active malignancy at Covid-19 diagnosis (66.7% TS, 61.6% VS). Among all 1,071 patients, deceased patients tended to categorize into poor risk groups for the NLR, PNI, mGPS, and PI (P<0.0001) with a return to pre-Covid-19 diagnosis NLR, PNI, and mGPS categorizations following recovery (P<0.01). In the TS, higher mortality rates were associated with NLR>6 (44.6% vs 28%, P<0.0001), PNI<40 (46.6% vs 20.9%, P<0.0001), mGPS (50.6% for mGPS2 vs 30.4% and 11.4% for mGPS1 and 0, P<0.0001), and PI (50% for PI2 vs 40% for PI1 and 9.1% for PI0, P<0.0001). Findings were confirmed in the VS (P<0.001 for all comparisons). Patients in poor risk categories had shorter median overall survival [OS], (NLR>6 30 days 95%CI 1-63, PNI<40 23 days 95%CI 10-35, mGPS2 20 days 95%CI 8-32, PI2 23 days 95%CI 1-56) compared to patients in good risk categories, for whom median OS was not reached (P<0.001 for all comparisons). The PLR was not associated with survival. Analyses of survival in the VS confirmed the NLR (P<0.0001), PNI (P<0.0001), PI (P<0.01), and mGPS (P<0.001) as predictors of survival. In a multivariable Cox regression model including all inflammatory indices and pre-established prognostic factors for severe Covid-19 including sex, age, comorbid burden, malignancy status, and receipt of anti-cancer therapy at Covid-19 diagnosis, the PNI was the only factor to emerge with a significant hazard ratio [HR] in both TS and VS analysis (TS HR 1.97, 95%CI 1.19-3.26, P=0.008;VS HR 2.48, 95%CI 1.47- 4.20, P=0.001). We conclude that systemic inflammation drives mortality from Covid-19 through hypoalbuminemia and lymphocytopenia as measured by the PNI and propose the PNI as the OnCovid Inflammatory Score (OIS) in this context.
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Background: Early reports from registry studies demonstrated high vulnerability of cancer patients from COVID-19, with case-fatality rates (CFR) >30% at the onset of the pandemic. With advances in disease management and increased testing capacity, the lethality of COVID-19 in cancer patients may have improved over time. Methods: The OnCovid registry lists European cancer patients consecutively diagnosed with COVID-19 in 35 centres from Jan 2020 to Feb 2021. We analysed clinical characteristics and outcomes stratified in 5 trimesters (Jan-Mar, Apr-Jun, Jul-Sep, Oct-Dec 2020 and Jan-Feb 2021) and studied predictors of mortality across 2 semesters (Jan-Jun 2020 and Jul 2020-Feb 2021). Results: At data cut-off, the 2634 eligible patients demonstrated significant time-dependant improvement in 14-days CFR with trimestral estimates of 29.8%, 20.3%, 12.5%, 17.2% and 14.5% (p<0.0001). Compared to the 2nd semester, patients diagnosed in the Jan-Jun 2020 time period were ≥65 (60.3% vs 56.1%, p=0.031) had ≥2 comorbidities (48.8% vs 42.4%, p=0.001) and non-advanced tumours (46.4% vs 56.1%, p<0.001). COVID-19 was more likely to be complicated in Jan-Jun 2020 (45.4% vs 33.9%, p<0.001), requiring hospitalization (59.8% vs 42.1%, p<0.001) and anti-COVID-19 therapy (61.7% vs 49.7%, p<0.001). The 14-days CFR for the 1st and 2nd semester was 25.6% vs 16.2% (p<0.0001), respectively. After adjusting for gender, age, comorbidities, tumour features, COVID-19 and anti-cancer therapy and COVID-19 complications, patients diagnosed in the 1st semester had an increased risk of death at 14 days (HR 1.68 [95%CI: 1.35-2.09]), but not at 3 months (HR 1.10 [95%CI: 0.94-1.29]) compared to those from the 2nd semester. Conclusions: We report a time-dependent improvement in the mortality from COVID-19 in European cancer patients. This may be explained by expanding testing capacity, improved healthcare resources and dynamic changes in community transmission over time. These findings are informative for clinical practice and policy making in the context of an unresolved pandemic. Clinical trial identification: NCT04393974. Legal entity responsible for the study: Imperial College London. Funding: Has not received any funding. Disclosure: D.J. Pinato: Financial Interests, Personal, Speaker’s Bureau: ViiV Healthcare;Financial Interests, Personal, Speaker’s Bureau: Bayer;Financial Interests, Personal, Advisory Board: EISAI;Financial Interests, Personal, Advisory Board: Roche;Financial Interests, Personal, Advisory Board: AstraZeneca. All other authors have declared no conflicts of interest.
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BACKGROUND: We aimed to describe the epidemiology, risk factors, and clinical outcomes of co-infections and superinfections in onco-hematological patients with COVID-19. METHODS: International, multicentre cohort study of cancer patients with COVID-19. All patients were included in the analysis of co-infections at diagnosis, while only patients admitted at least 48 h were included in the analysis of superinfections. RESULTS: 684 patients were included (384 with solid tumors and 300 with hematological malignancies). Co-infections and superinfections were documented in 7.8% (54/684) and 19.1% (113/590) of patients, respectively. Lower respiratory tract infections were the most frequent infectious complications, most often caused by Streptococcus pneumoniae and Pseudomonas aeruginosa. Only seven patients developed opportunistic infections. Compared to patients without infectious complications, those with infections had worse outcomes, with high rates of acute respiratory distress syndrome, intensive care unit (ICU) admission, and case-fatality rates. Neutropenia, ICU admission and high levels of C-reactive protein (CRP) were independent risk factors for infections. CONCLUSIONS: Infectious complications in cancer patients with COVID-19 were lower than expected, affecting mainly neutropenic patients with high levels of CRP and/or ICU admission. The rate of opportunistic infections was unexpectedly low. The use of empiric antimicrobials in cancer patients with COVID-19 needs to be optimized.
Subject(s)
COVID-19 , Coinfection , Neoplasms , Superinfection , Cohort Studies , Coinfection/epidemiology , Humans , Intensive Care Units , Neoplasms/complications , Neoplasms/epidemiology , SARS-CoV-2ABSTRACT
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.
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Background: The severity of SARS-CoV-2 infection (COVID-19) is predicted by advancing age and co-morbidities. The relative contribution of cancer in influencing the course of COVID-19 is poorly understood. We designed the OnCOVID study to investigate natural history of COVID-19 disease in cancer patients. Methods: This retrospective, multi-center observational study conducted across 8 tertiary centers in Europe recruited cancer patients aged >/= 18 and diagnosed with COVID-19 between February 26th and April 1st, 2020. Descriptive statistics, univariable and multivariable Cox regression models were used to assess patient’s main characteristics and to evaluate the factors associated to COVID-19 related mortality. Results: We identified 204 patients from United Kingdom (n=97, 48%), Italy (n=56, 27%) and Spain (n=51, 25%). Most patients were male (n=127, 62%) had a diagnosis of solid malignancy (n=184, 91%) and 103 (51%) had non-metastatic disease. Mean (±SD) patient age was 69±13 years, and 161 (79%) had >/= 1 co-morbidity, most commonly hypertension (n=88, 43%) and diabetes (n=46, 23%). Commonest presenting symptoms were fever (n=136, 67%) and cough (n=119, 58%), beginning 3.8 (±4.5 SD) days before diagnosis. Most patients (n=141, 69%) had >/= 1 complication from COVID-19, including respiratory failure (n=128, 63%) and acute respiratory distress syndrome (n=49, 24%). In total, 36 patients (19%) patients were escalated to high-dependency or intensive care. At time of analysis, 59 patients had died (29%), 53 were discharged from hospital (26%) and 92 (45%) were in-hospital survivors. Mortality was higher in patients aged >/= 65 (36% versus 16%), in those with >/= 2 co-morbidities (40% versus 18%) and developing >/= 1 complication from COVID-19 (38% versus 4%, p=0.004). Multi-variable analyses confirmed age >/= 65 and >/= 2 co-morbidities to predict for patient mortality independent of tumor stage, active malignancy or anti-cancer therapy. Conclusions: In the early outbreak of SARS-CoV-2 infection in Europe co-morbid burden and advancing age predicted for adverse disease course in cancer patients. Risk stratification based on these factors should inform personalized oncological decision making during the COVID-19 pandemic. Legal entity responsible for the study: Imperial College London. Funding: Has not received any funding. Disclosure: D.J. Pinato: Speaker Bureau/Expert testimony, received lecture fees : ViiV Healthcare;Speaker Bureau/Expert testimony, received lecture fees : Bayer Healthcare;Travel/Accommodation/Expenses: BMS;Advisory/Consultancy: Mina Therapeutics;EISAI;Roche;Astra Zeneca;Research grant/Funding (institution): MSD;BMS. A. Patriarca: Advisory/Consultancy: Takeda;Sanofi. G. Gaidano: Advisory/Consultancy, Speaker Bureau/Expert testimony: Janssen;Abbvie;Advisory/Consultancy: AstraZeneca;Sunesys. J. Brunet: Advisory/Consultancy: MSD;AstraZeneca. J. Tabernero: Advisory/Consultancy: Array Biopharma;Astra Zeneca;Bayer;Beigene;Boehringer Ingelheim;Chugai;Genentech;GenMab;Halozyme;Inflection Biosciences Limited;Ipsen;Kura;Lilly;MSD;Menarini;Merck Serono;Merrimack;Merus;Molecular Partners;Novartis;Peptomics;Pfizer;Pharmacyclics;Rafael Pharmaceuticals;ProteoDesign SL;F. Hoffmann-La Roche Ltd;Sanofi;Servier;Seagen;Symphogen, Taiho, VCN Biosciences, Biocartis, Foundation Medicine, HalioDX SAS and Roche Diagnostics. A. Prat:Honoraria (self), Advisory/Consultancy: Pfeizer;Honoraria (self), Advisory/Consultancy, Research grant/Funding (self): Novartis;Roche;Honoraria (self): MSD Oncology;Lilly;Honoraria (self), Travel/Accommodation/Expenses: Daiichi Sankyo;Advisory/Consultancy: BMS;Amgen;NanoString Technologies. A. Gennari: Advisory/Consultancy, Speaker Bureau/Expert testimony, Research grant/Funding (self): Roche;Eli Lilly;EISAI;Advisory/Consultancy: Pierre Fabre;MSD;Novartis;Advisory/Consultancy, Speaker Bureau/Expert testimony: Daiichi Sankyo;Speaker Bureau/Expert testimony: Teva;Gentili;Pfizer;AstraZeneca;Celgene. All other authors have declared no onflicts 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.
ABSTRACT
Background: SARS-CoV-2 outbreak has impacted on the management of oncological p, leading to treatment delays in a considerable number of cases. The aim of this study was to evaluate if oncological T affected negatively COVID-19 outcome. Methods: We retrospectively analyzed clinical data from p with solid tumors under active systemic T (received in the last 6 months) that were diagnosed with SARS-CoV-2 infection (defined as positive PCR) between March and 11th May 2020 in our center. Study endpoint was death due to COVID-19. We divided the patients in two groups;those who had received treatment in the last 4 weeks and those who had not. Descriptive and univariate analysis were performed to detect the effect of T type and other variables on COVID-19 related mortality. Results: A total of 70 p were included with a median follow-up of 28 days (10-47) and active oncological T had been administered in the past 4 weeks to 44 p. Median age was 66 (IQR 56-74), 23 p (52.27%) were female and 41 (93.2%) had a baseline ECOG≤1. The most frequent primary site was lung tumor (12 p [27.3%]), followed by breast (11 p [25%]) and gastrointestinal (5 p [11.4%]). Thirty-one p (70.5%) had metastatic disease and 13 (29.5%) were included in clinical trials. Twenty-four p (54.5%) received chemotherapy (CT), 14 (31.8%) targeted therapies, 9 (20.4%) immunotherapy (IT), 5 (11.4%) radiotherapy and 6 (13.6%) hormonotherapy. A total of 13 p (29.5%) received different combinations of oncological T. Death due to COVID-19 occurred in 5/22 (22.7%) p receiving CT and 6/21 (28.5%) p in the non-CT (p>0.05). Only 1/9 (11.1%) p treated with IT died compared to 11/35 (31.4%) p in the rest of the cohort (p>0.05). Age>71, comorbidities such as chronic obstructive pulmonary disease and ECOG status>2 were associated to a higher mortality. The distribution of these variables between the anticancer T groups was not different. Conclusions: Our results suggest that CT and other anticancer T might not worsen COVID-19 related mortality;nevertheless, the number of patients was small. and decision making has to be individualized. Our findings may warrant further investigation in larger studies. Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: E. Felip: Advisory/Consultancy, Speaker Bureau/Expert testimony: AbbVie;AstraZeneca;Blueprint medicines;Boehringer Ingelheim;Bristol-Myers Squibb;Celgene;Eli Lilly;Guardant Health;Janssen;Medscape;Merck KGaA;Novartis;Pfizer;Roche;Takeda;Touchtime;Research grant/Funding (self), Research grant/Funding (institution): Fundación Merck Salud;Oncology Innovation EMD Serono. J. Carles: Advisory/Consultancy, Speaker Bureau/Expert testimony: Johnson & Johnson;Bayer;Advisory/Consultancy, Speaker Bureau/Expert testimony, Research grant/Funding (self): Astellas Pharma;Advisory/Consultancy: Pfizer;Sanofi;MSD Oncology;Advisory/Consultancy, Research grant/Funding (self): Roche;Advisory/Consultancy, Research grant/Funding (self), Travel/Accommodation/Expenses: AstraZéneca;Speaker Bureau/Expert testimony: Asofarma;Research grant/Funding (self), Travel/Accommodation/Expenses: BMS;ravel/Accommodation/Expenses: Ipsen;Roche;Research grant/Funding (self): AB Science;Aragon Pharmaceuticals;Pharmaceuticals;INC;Blueprint Medicines Corporation;N Immunotherapeutics INC;Boehringer Ingelheim España, S.A.;Clovis Oncology;Cougar Biotechnology INC;Deciphera Pharmaceuticals LLC;Exelixis INC;F. Hoffmann-La Roche LTD;Genentech INC;Glaxosmithkline;Incyte Corporation;Janssen-Cilag International NV;Karyopharm Therapeutics INC;Laboratoires Leurquin Mediolanum SAS. J. Tabernero: Honoraria (self): Array Biopharma;AstraZeneca;Bayer;BeiGene;Boehringer Ingelheim;Chugai;Genentech;Genmab A/S;Halozyme;Imugene Limited;Inflection Biosciences Limited;Ipsen;Kura Oncology;Lilly;MSD;Merck Serono;Menarini;Merrimack;Merus;Molecular Partners;Novartis;Peptomyc;Pfizer;Pharmacyclics;ProteoDesign SL;Rafael Pharmaceuticals;F. Hoffmann-La Roche Ltd;): Sanofi;eaGen;Seattle Genetics, Servier, Symphogen, Taiho, VCN Biosciences, Biocartis, Foundation Medicine, HalioDX SAS and Roche Diagnostics. All other authors have declared no conflicts of interest.