Food security and fruit and vegetable consumption among preschoolers: an exploratory study during the COVID-19 pandemic

Studies that assess food insecurity and its association with the consumption of fruits, legumes, and vegetables (FLV) can help identify groups and risk factors of inadequate food consumption, in order to propose assertive nutritional interventions. The aim of this study was to describe FLV consumption by children in different food security situations. This is an exploratory cross-sectional study, conducted with parents/guardians of 44 children from zero to four years old. The short version of the Brazilian Food Insecurity Scale and a Food Frequency Questionnaire were applied to parents/guardians via a telephone interview. The children were 2.6 years old on average, 56.8% were female, 67.5% were eutrophic, and 70.5% of the families were in a situation of food insecurity. For households in a situation of food security, the median consumption of FLV was 213.4 g/day (P25=97.89;P75=425.91). As for those in a situation of food insecurity, the median FLV was 105.4 g/day (P25=33.58;P75=205.16). It was concluded that the consumption of FLV by children from families in a situation of food security is higher than that of children in a situation of food insecurity, who are strongly influenced by the offer of cheap food with low nutritional quality. Public policies are needed to favor the guarantee of access to FLV of quality and at an affordable cost for all families.

The FLARE score, circulating neutrophils, and association with COVID-19 outcomes in patients with solid tumors

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).

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.

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.

Change of circulating pro-inflammatory markers between pre-COVID-19 condition and COVID-19 diagnosis predicts early death in cancer patients: The FLARE score

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.

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.