The acute phase response identifies cancer patients with adverse outcomes from SARS-CoV-2 infection as quantified by the OnCovid Inflammatory Score

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.

SARS-CoV-2 antibody seroprevalence and safety of vaccines in cancer patients who recovered from COVID-19

Background: Little is known about natural anti-SARS-CoV-2 antibody seroprevalence post COVID-19 and safety of vaccines in COVID-19 survivors with cancer. Methods: Among 2795 consecutive patients (pts) with COVID-19 and cancer registered to OnCovid between 01/2020 and 02/2021, we examined natural seroprevalence of anti-SARS-CoV-2 Antibodies (SC2Ab, IgM or IgG) in pts tested post-infection. We analysed prevalence and safety of SARS-Cov-2 vaccine administration in pts who underwent clinical re-assessment at participating institutions. Results: Out of 350 pts tested for SC2Ab, 318 (90.9%) had a positive SC2Ab titre post-convalescence. Neither baseline features (sex, age, comorbidities, smoking history, tumour stage/status, anticancer-therapy and primary tumour) nor COVID-19-specific features (complications, hospitalization, sequelae) were significantly associated SC2Ab status. Receipt of COVID-19 specific therapy was higher among SC2Ab+ pts (62.6% vs 40.6%, p=0.0156). Out of 593 pts with known vaccination status, 178 (30%) had received 1 dose, whilst 38 pts (6.4%) received 2 doses of mRNA based (70.2%) or viral vector vaccine (17.4%). Vaccinated pts were more likely aged ≥65 years (59% vs 48.3%, p=0.0172), with loco-regional tumour stage (56% vs 40.8%, p=0.0014), on anti-cancer therapy at COVID-19 (49.1% vs 38.2%, p=0.0168) and history of prior hospitalisation due to COVID-19 (61.8% vs 48.3%, p=0.0029). Vaccine-related adverse events were reported for 18/56 evaluable pts (32.1%) and included injection site reactions (50%), fever (44.4%), arthralgias (33.3%), fatigue (33.3%) and allergy (5.5%). No long-term vaccine-related morbidity was reported. Conclusions: We report high seroprevalence (>90%) of SC2Ab in convalescent cancer pts who survived COVID-19 irrespective of baseline demographics, oncological characteristics and COVID-19 severity. COVID-19 vaccines appear to be safe in cancer pts with history of prior infection. 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, Invited Speaker: ViiV Healthcare;Financial Interests, Personal, Invited Speaker: Bayer;Financial Interests, Personal, Advisory Board: Eisai;Financial Interests, Personal, Advisory Board: Amgen;Financial Interests, Personal, Advisory Board: BMS;Financial Interests, Personal, Advisory Board: Pfizer;Financial Interests, Personal, Advisory Board: Nanostring tech. A. Cortellini: Financial Interests, Personal, Advisory Board: MSD;Financial Interests, Personal, Advisory Board: BMS;Financial Interests, Personal, Advisory Board: Roche;Financial Interests, Personal, Invited Speaker: Novartis;Financial Interests, Personal, Advisory Board: SunPharma;Financial Interests, Personal, Invited Speaker: AstraZeneca;Financial Interests, Personal, Invited Speaker: Astellas. All other authors have declared no conflicts of interest.

The fiscal cost of the provision of basic public services, subsidies for expenditure on food and basic citizen income per household in costa rica, guatemala and el salvador during the covid-19 pandemic: An expenditure analysis

The objective of this article is to estimate the fiscal costs, using income and expenditure surveys, of the provision of basic public services (electricity, water, telephone and internet) for the 40% of the population with the lowest incomes, the provision of a subsidy of 50% of actual food expenditure for the 40% of the population with the lowest incomes and the provision of a basic income per household equivalent to the value of the poverty line for households under the poverty line in Costa Rica, Guatemala and El Salvador during the COVID-19 pandemic. These fiscal options are a fundamental component of any public health strategy against the COVID-19 considering they give economic viability to the population during the isolation and mobility restrictions period and financial support during the economic and social emergency. The results show that the fiscal costs of the provision of basic public services to 40% of the population with the lowest incomes or other fiscal measures considering less ambitious targets are heterogeneous between these Central American countries because of previous conditions and public policies but are reasonable and possible to cover under the actual circumstances. © 2020, Centro de Investigacion y Docencia Economicas A.C.. All rights reserved.

First results of the COCO study: COVID-19 outcomes in patients with cancer

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.

Determinants of mortality from SARS-CoV-2 infection in European cancer patients

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.

Active smoking and severity of COVID-19 infection in cancer patients

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.

Expanding the role of medical oncologist in the management of COVID-19

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.