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Background: Data from the first wave of COVID-19 infection demonstrated that a history of cancer and SACT was associated with poorer outcomes. Our study compares outcomes for cancer patients matched to non-cancer patients between the two waves in order to explore further how cancer and its treatment may impact COVID-19 mortality. Methods: Data was collected for patients with positive PCR and history of cancer between 1 Mar to 20 May 2020 and 1 Dec to 8 Feb 2021 for wave 1 and 2, respectively. A contemporaneous cohort of patients without cancer were age- and sex-matched for comparison. Results: The total number of patients presenting with COVID-19 was higher in wave two (1135 vs 626). 207 of these patients had cancer, and were matched to 452 patients without cancer from both waves. There was a significantly improved chance of mortality in wave 2 (HR 0.41, p < 0.0001). When adjusting for age, sex and co-morbidities, cancer was an independent risk factor for mortality amongst patients hospitalised with COVID-19 in wave 1 (HR 1.62, p = 0.02), but not in wave 2. There was a trend towards improved survival for hospitalised patients in wave 2 receiving COVID-19 specific treatment including dexamethasone, remdesivir, tocilizumab (HR 0.75, p = 0.086). For the combined cancer cohort, SACT was an independent predictor of mortality, as was metastatic disease. [Formula presented] Conclusions: The mortality for both cancer and non-cancer patients improved between waves of the pandemic. Advances in detection, prevention and treatment may account for this. Cancer was no longer a risk factor for mortality in the second wave, however SACT and metastatic cancer remained risk factors for mortality within the cancer cohort. This emphasises the need for ongoing protection of patients with advanced cancer and those on SACT, including through their prioritisation for COVID-19 vaccination globally. Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: H. Shaw: Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: Novartis;Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: BMS;Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: MSD;Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: Immunocore;Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: Idera;Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: Iovance;Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: Sanofi Genzyme/Regeneron;Financial Interests, Personal, Invited Speaker, Advisory/Consultancy: Macrogenics;Financi Interests, Personal, Invited Speaker, Advisory/Consultancy: Roche. R. Roylance: Financial Interests, Personal, Other, Personal Fees: Novartis;Financial Interests, Personal, Other, Personal Fees & None-financial support: Daiichi Sankyo;Financial Interests, Personal, Other, Personal Fees: Eli-Lilly;Financial Interests, Personal, Other, Personal Fees: Pfizer;Financial Interests, Personal, Other, Personal Fees & None-financial support: G1 Therapeutics;Non-Financial Interests, Personal, Other, None-financial support: Roche;Non-Financial Interests, Personal, Other, None-financial support: AstraZeneca. All other authors have declared no conflicts of interest.

Background Systemic inflammation is a unifying mechanism common to cancer progression and SARS-CoV-2 infection. Mortality from Covid-19 strongly relates to systemic inflammatory reaction to SARS-CoV-2. We sought to determine whether inflammatory biomarkers can identify poor outcome in cancer patients with Covid-19. Methods Between 27/02 and 23/06/2020, OnCovid retrospectively accrued 1,318 consecutive Covid-19-infected cancer patients aged >18 from 25 academic centers in the U.K., Spain, Italy, Germany and Belgium. Patients with leukemia, myeloma or insufficient data were excluded. We tested neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), prognostic nutritional index (PNI), modified Glasgow prognostic score (mGPS), and prognostic index (PI) as prognostic biomarkers. NLR, PLR and PNI were dichotomized around their medians. Results 1,071 eligible patients were sorted into a training set (TS, n=529) and validation set (VS, n=542). TS and VS were matched by age (67.9±13.3 TS, 68.5±13.5 VS), active malignancy at Covid-19 diagnosis (66.7% TS, 61.6% VS), presence of >1 comorbidity (52.1% TS, 49.8% VS) and prevalence of complications including respiratory failure (58.0% TS, 59.0% VS) and ARDS (11.5% TS, 12.9% VS). In the TS, higher mortality rates were associated with NLR>6 (44.6% vs 28%, p 6 30 days 95%CI 1-63, PNI

Background: The COVID-19 pandemic remains of pressing concern for patients with cancer Mortality from COVID-19 is predicted by age and co-morbidities, but the relative contribution of cancer is poorly understood As a tertiary academic hospital serving a large general and cancer population in a COVID-19 epicentre, we are uniquely placed to investigate this We report data from our study, comparing cancer patients to an age- and sex-matched non-cancer cohort Methods: Patients with laboratory confirmed COVID-19 from 1 March to 31 May 2020 were included Patients with a history of solid cancer were compared to an age- and sex-matched non-cancer cohort Patients with haematological malignancies were excluded Results: We identified 94 patients with cancer and 226 patients without cancer In univariate analysis, age, South Asian ethnicity and co-morbidities predicted mortality (see table) More in the cancer cohort had died compared to the non-cancer cohort (43 6% vs 34 1%) The higher mortality among cancer patients was statistically significant among those aged 70 years and above (OR 2 28, 1 14-4 50, p = 0 02) After adjusting for age, ethnicity and co-morbidities, a history of cancer was an independent predictor of mortality following COVID-19 (HR 1 57, 95% CI:1 04-2 4, p = 0 03) Patients with active malignancy also had similarly increased adjusted mortality (HR 1 64, 95% CI: 1 03 – 2 6, p = 0 04) Increasing age (HR 1 49 every 10 years, 95% CI:1 25-1 8, p

Background The COVID-19 (C19) pandemic has prompted alterations to systemic anti-cancer therapy (SACT) due to concerns of immunosuppression and healthcare exposure. However, the effects of SACT on mortality in patients who acquire C19 are not well understood. As a national cancer centre within a major C19 hotspot, we seek to address these risks at scale. Methods Patients with a history of solid cancers and laboratory confirmed C19 (1 Mar to 31 May 2020) were included. Haematological malignancies were excluded. The primary outcome was time from C19 diagnosis to death. The last follow-up date was 22 Jun 2020. Results We identified 94 cancer patients; 62 males (median age 73, BMI 24.9), and 32 females (median age 68.5, BMI 25.7). Genitourinary (n = 24) cancers were the most common, followed by gastrointestinal (n = 23), thoracic (n = 15), and gynaecological (n = 9) cancers. 25 patients received SACT: chemotherapy (n = 15), endocrine therapy (n = 8), immunotherapy (n = 4), and targeted anti-cancer therapy (n = 2). 16 patients received SACT with palliative intent. Patients on SACT had a greater incidence of metastatic disease (48.0% vs 10.6%, p

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 conflicts of interest.