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.

Systemic anti-cancer therapy and metastatic cancer are independent mortality risk factors during two UK waves of the COVID-19 pandemic at University College London Hospital

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.

#HBLTable: A Cost-Effective Study-From-Home Furniture Solution for Low-Income Families Impacted by COVID-19

The COVID-19 pandemic has abruptly forced schools worldwide to implement Home Based Learning (HBL) due to countries going into lockdown and quarantine. Chemistry Team thus developed the #HBLTable, a height adjustable cardboard table meant for underprivileged families that struggle with space and the necessary furnishing to facilitate conducive learning for their children at home. The conducted research indicated that the prevalent challenges surrounding HBL were: (1) posture and ergonomics for a child and (2) children quickly outgrowing furniture built for their height. The #HBLTable was thus designed to cater for two heights - allowing users to adjust between the heights by simply flipping and rotating the table. The table comes equipped with a tablet and laptop stand to reduce poor posture as well. Beyond uncovering the context and motivations, this paper details the research and design process behind the construction of the #HBLTable. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

COVID-19 mortality in patients receiving anti-cancer therapy in a UK national cancer centre

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. Method(s): 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. Result(s): 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 0.001) and were younger (median age 62.5 vs 73.0, p = 0.01). They were also more likely to have renal impairment (p = 0.02), lymphopaenia (p = 0.01) and anaemia (p = 0.04) compared to those not on SACT. The univariate analysis showed age and co-morbidities were associated with mortality (Table). Adjusting for age, ethnicity, co-morbidities and the presence of metastatic cancer, SACT was an independent risk factor for C19 mortality (HR 2.46, 1.09 - 5.5, p = 0.03). Age, South Asian ethnicity, hypertension and cerebrovascular disease were also independent risk factors for C19 mortality. [Formula presented] Conclusion(s): C19 infection poses a substantial risk to cancer patients and our data suggests that SACT is an independent risk factor for mortality in C19 infection. These findings call for a nuanced approach to C19 risk, focusing on established risk factors such as age and co-morbidities to guide treatment decisions. Legal entity responsible for the study: University College London Hospital. Funding(s): Has not received any funding. Disclosure: All authors have declared no conflicts of interest. Copyright © 2020

Do cancer patients really do worse? A study in a UK tertiary hospital within a COVID-19 epicentre

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 <0.001), South Asian ethnicity (HR 2.92, 95% CI:1.73-4.9, p <0.001) and cerebrovascular disease (HR 1.93, 95% CI:1.18-3.2, p = 0.008) were also confirmed as independent predictors of mortality. [Formula presented] Conclusions: Along with known risk factors, cancer confers an independent risk for mortality in COVID-19. Taken together, our findings support the need to continue ‘shielding’ patients with cancer from exposure to COVID-19 infection. Increasing age and co-morbidity should take precedence when weighing up risk factors for severe COVID-19 infection in cancer patients. Legal entity responsible for the study: University College London Hospitals NHS Foundation Trust. Funding: Has not received any funding. Disclosure: H.M. Shaw: Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis, BMS, MSD;Advisory/Consultancy: Immunocore, Idera, Iovance, Genmab, Sanofi Genzyme/Regeneron, Macrogenics, Roche;Speaker Bureau/Expert testimony: Sanofi Genzyme. 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.