ABSTRACT
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.
ABSTRACT
Background: There is uncertainty as to the contribution of cancer patients' features on severity and mortality from Covid-19 and little guidance as to the role of anti-cancer and anti-Covid-19 therapy in this population. Method(s): OnCovid is a retrospective observational study conducted across 19 European centers that recruited cancer patients aged >18 and diagnosed with Covid-19 between 26/02 and 01/04/2020. Uni- and multivariable regression models were used to evaluate predictors of Covid-19 severity and mortality. Result(s): We identified 890 patients from UK (n=218, 24%), Italy (n=343, 37%), Spain (n=323, 36%) and Germany (n=6, 1%). Most patients were male (n=503, 56%) had a diagnosis of solid malignancy (n=753, 84%) and 556 (62%) had active disease. Mean (+/-SD) patient age was 68+/-13 years, and 670 (75%) had >1 co-morbidity, most commonly hypertension (n=386, 43%). Commonest presenting symptoms were fever (n=569, 63%) and cough (n=448, 50%), beginning 6.3 (+/-9.5 SD) days before diagnosis. Most patients (n=565, 63%) had >1 complication from Covid-19, including respiratory failure (n=527, 59%) and acute respiratory distress syndrome (n=127, 22%). In total, 110 patients (14%) were escalated to high-dependency or intensive care. At time of analysis, 299 patients had died (33%). Multi-variate logistic regression identified male gender, age>65 (p<0.0001) presence of >2 comorbidities (p=0.001) active malignancy (p=0.07) as predictors of complicated Covid-19. Mortality was associated with active malignancy (p<0.0001), age>65 and co-morbid burden (p=0.002). Provision of chemotherapy, targeted therapy or immunotherapy was not associated with higher mortality. Exposure to anti-malarials alone (chloroquine/hydroxychloroquine, n=182, p<0.001) or in combination with anti-virals (n=195, p<0.001) or tocilizumab (n=51, p=0.004) was associated with improved mortality compared to patients who did not receive any of these therapies (n=446) independent of patients' gender, age, tumour stage and severity of Covid-19. Conclusion(s): This study highlights the clinical utility of demographic factors for individualized risk-stratification of patients and supports further research into emerging anti Covid-19 therapeutics in SARS-Cov-2 infected cancer patients. Clinical trial identification: NCT04393974. Legal entity responsible for the study: Imperial College London. Funding(s): Has not received any funding. Disclosure: D.J. Pinato: Speaker Bureau/Expert testimony: ViiV Healthcare;Advisory/Consultancy, Travel/Accommodation/Expenses: Bayer;Advisory/Consultancy, Speaker Bureau/Expert testimony, Research grant/Funding (institution), Travel/Accommodation/Expenses: BMS;Honoraria (self), Advisory/Consultancy: MiNa Therapeutics;Advisory/Consultancy: Eisai;Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche;Advisory/Consultancy: AstraZeneca;Research grant/Funding (institution): MSD. All other authors have declared no conflicts of interest.Copyright © 2020 European Society for Medical Oncology
ABSTRACT
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.
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.