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      SARS-CoV-2 Virus in Cancer Patients: A New Unknown in an Unsolved Equation

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          Abstract

          Introduction

          Cancer patients are more susceptible to infections, and infection can be more severe than in patients without cancer diagnosis. We conducted this retrospective study in patients admitted for SARS-CoV-2 infection in order to find differences in inflammatory markers and mortality in cancer patients compared to others.

          Methods

          We reviewed the electronic records of patients admitted for SARS-CoV-2 infection confirmed by PCR from March to September 2020. Data on socio-demographics, comorbidities, inflammatory makers, and cancer-related features were analyzed.

          Results

          2,772 patients were admitted for SARS-CoV-2, to the Hospital Universitario Ramón y Cajal in Madrid during this period. Of these, 2,527 (91%) had no history of neoplastic disease, 164 (5.9%) patients had a prior history of cancer but were not undergoing oncological treatment at the time of infection, and 81 (2.9%) were in active treatment. Mortality in patients without a history of cancer was 19.5%, 28.6% for patients with a prior history of cancer, and 34% in patients with active cancer treatment. Patients in active oncology treatment with the highest mortality rate were those diagnosed with lung cancer (OR 5.6 95% CI: 2.2–14.1). In the multivariate study, active oncological treatment (OR 2.259 95% CI: 1.35–3.77) and chemotherapy treatment (OR 3.624 95% CI: 1.17–11.17), were statistically significant factors for the risk of death for the whole group and for the group with active oncological treatment, respectively.

          Conclusion

          Cancer patients on active systemic treatment have an increased risk of mortality after SARS-CoV-2 infection, especially with lung cancer or chemotherapy treatment.

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          Most cited references35

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China

            China and the rest of the world are experiencing an outbreak of a novel betacoronavirus known as severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). 1 By Feb 12, 2020, the rapid spread of the virus had caused 42 747 cases and 1017 deaths in China and cases have been reported in 25 countries, including the USA, Japan, and Spain. WHO has declared 2019 novel coronavirus disease (COVID-19), caused by SARS-CoV-2, a public health emergency of international concern. In contrast to severe acute respiratory system coronavirus and Middle East respiratory syndrome coronavirus, more deaths from COVID-19 have been caused by multiple organ dysfunction syndrome rather than respiratory failure, 2 which might be attributable to the widespread distribution of angiotensin converting enzyme 2—the functional receptor for SARS-CoV-2—in multiple organs.3, 4 Patients with cancer are more susceptible to infection than individuals without cancer because of their systemic immunosuppressive state caused by the malignancy and anticancer treatments, such as chemotherapy or surgery.5, 6, 7, 8 Therefore, these patients might be at increased risk of COVID-19 and have a poorer prognosis. On behalf of the National Clinical Research Center for Respiratory Disease, we worked together with the National Health Commission of the People's Republic of China to establish a prospective cohort to monitor COVID-19 cases throughout China. As of the data cutoff on Jan 31, 2020, we have collected and analysed 2007 cases from 575 hospitals (appendix pp 4–9 for a full list) in 31 provincial administrative regions. All cases were diagnosed with laboratory-confirmed COVID-19 acute respiratory disease and were admitted to hospital. We excluded 417 cases because of insufficient records of previous disease history. 18 (1%; 95% CI 0·61–1·65) of 1590 COVID-19 cases had a history of cancer, which seems to be higher than the incidence of cancer in the overall Chinese population (285·83 [0·29%] per 100 000 people, according to 2015 cancer epidemiology statistics 9 ). Detailed information about the 18 patients with cancer with COVID-19 is summarised in the appendix (p 1). Lung cancer was the most frequent type (five [28%] of 18 patients). Four (25%) of 16 patients (two of the 18 patients had unknown treatment status) with cancer with COVID-19 had received chemotherapy or surgery within the past month, and the other 12 (25%) patients were cancer survivors in routine follow-up after primary resection. Compared with patients without cancer, patients with cancer were older (mean age 63·1 years [SD 12·1] vs 48·7 years [16·2]), more likely to have a history of smoking (four [22%] of 18 patients vs 107 [7%] of 1572 patients), had more polypnea (eight [47%] of 17 patients vs 323 [23%] of 1377 patients; some data were missing on polypnea), and more severe baseline CT manifestation (17 [94%] of 18 patients vs 1113 [71%] of 1572 patients), but had no significant differences in sex, other baseline symptoms, other comorbidities, or baseline severity of x-ray (appendix p 2). Most importantly, patients with cancer were observed to have a higher risk of severe events (a composite endpoint defined as the percentage of patients being admitted to the intensive care unit requiring invasive ventilation, or death) compared with patients without cancer (seven [39%] of 18 patients vs 124 [8%] of 1572 patients; Fisher's exact p=0·0003). We observed similar results when the severe events were defined both by the above objective events and physician evaluation (nine [50%] of 18 patients vs 245 [16%] of 1572 patients; Fisher's exact p=0·0008). Moreover, patients who underwent chemotherapy or surgery in the past month had a numerically higher risk (three [75%] of four patients) of clinically severe events than did those not receiving chemotherapy or surgery (six [43%] of 14 patients; figure ). These odds were further confirmed by logistic regression (odds ratio [OR] 5·34, 95% CI 1·80–16·18; p=0·0026) after adjusting for other risk factors, including age, smoking history, and other comorbidities. Cancer history represented the highest risk for severe events (appendix p 3). Among patients with cancer, older age was the only risk factor for severe events (OR 1·43, 95% CI 0·97–2·12; p=0·072). Patients with lung cancer did not have a higher probability of severe events compared with patients with other cancer types (one [20%] of five patients with lung cancer vs eight [62%] of 13 patients with other types of cancer; p=0·294). Additionally, we used a Cox regression model to evaluate the time-dependent hazards of developing severe events, and found that patients with cancer deteriorated more rapidly than those without cancer (median time to severe events 13 days [IQR 6–15] vs 43 days [20–not reached]; p<0·0001; hazard ratio 3·56, 95% CI 1·65–7·69, after adjusting for age; figure). Figure Severe events in patients without cancer, cancer survivors, and patients with cancer (A) and risks of developing severe events for patients with cancer and patients without cancer (B) ICU=intensive care unit. In this study, we analysed the risk for severe COVID-19 in patients with cancer for the first time, to our knowledge; only by nationwide analysis can we follow up patients with rare but important comorbidities, such as cancer. We found that patients with cancer might have a higher risk of COVID-19 than individuals without cancer. Additionally, we showed that patients with cancer had poorer outcomes from COVID-19, providing a timely reminder to physicians that more intensive attention should be paid to patients with cancer, in case of rapid deterioration. Therefore, we propose three major strategies for patients with cancer in this COVID-19 crisis, and in future attacks of severe infectious diseases. First, an intentional postponing of adjuvant chemotherapy or elective surgery for stable cancer should be considered in endemic areas. Second, stronger personal protection provisions should be made for patients with cancer or cancer survivors. Third, more intensive surveillance or treatment should be considered when patients with cancer are infected with SARS-CoV-2, especially in older patients or those with other comorbidities.
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              Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study

              Summary Background Data on patients with COVID-19 who have cancer are lacking. Here we characterise the outcomes of a cohort of patients with cancer and COVID-19 and identify potential prognostic factors for mortality and severe illness. Methods In this cohort study, we collected de-identified data on patients with active or previous malignancy, aged 18 years and older, with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from the USA, Canada, and Spain from the COVID-19 and Cancer Consortium (CCC19) database for whom baseline data were added between March 17 and April 16, 2020. We collected data on baseline clinical conditions, medications, cancer diagnosis and treatment, and COVID-19 disease course. The primary endpoint was all-cause mortality within 30 days of diagnosis of COVID-19. We assessed the association between the outcome and potential prognostic variables using logistic regression analyses, partially adjusted for age, sex, smoking status, and obesity. This study is registered with ClinicalTrials.gov, NCT04354701, and is ongoing. Findings Of 1035 records entered into the CCC19 database during the study period, 928 patients met inclusion criteria for our analysis. Median age was 66 years (IQR 57–76), 279 (30%) were aged 75 years or older, and 468 (50%) patients were male. The most prevalent malignancies were breast (191 [21%]) and prostate (152 [16%]). 366 (39%) patients were on active anticancer treatment, and 396 (43%) had active (measurable) cancer. At analysis (May 7, 2020), 121 (13%) patients had died. In logistic regression analysis, independent factors associated with increased 30-day mortality, after partial adjustment, were: increased age (per 10 years; partially adjusted odds ratio 1·84, 95% CI 1·53–2·21), male sex (1·63, 1·07–2·48), smoking status (former smoker vs never smoked: 1·60, 1·03–2·47), number of comorbidities (two vs none: 4·50, 1·33–15·28), Eastern Cooperative Oncology Group performance status of 2 or higher (status of 2 vs 0 or 1: 3·89, 2·11–7·18), active cancer (progressing vs remission: 5·20, 2·77–9·77), and receipt of azithromycin plus hydroxychloroquine (vs treatment with neither: 2·93, 1·79–4·79; confounding by indication cannot be excluded). Compared with residence in the US-Northeast, residence in Canada (0·24, 0·07–0·84) or the US-Midwest (0·50, 0·28–0·90) were associated with decreased 30-day all-cause mortality. Race and ethnicity, obesity status, cancer type, type of anticancer therapy, and recent surgery were not associated with mortality. Interpretation Among patients with cancer and COVID-19, 30-day all-cause mortality was high and associated with general risk factors and risk factors unique to patients with cancer. Longer follow-up is needed to better understand the effect of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments. Funding American Cancer Society, National Institutes of Health, and Hope Foundation for Cancer Research.
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                Author and article information

                Journal
                Oncology
                Oncology
                OCL
                Oncology
                S. Karger AG (Allschwilerstrasse 10, P.O. Box · Postfach · Case postale, CH–4009, Basel, Switzerland · Schweiz · Suisse, Phone: +41 61 306 11 11, Fax: +41 61 306 12 34, karger@karger.com )
                0030-2414
                1423-0232
                5 September 2022
                5 September 2022
                : 1-11
                Affiliations
                [1] aRadiation Oncology Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [2] bInfectious Diseases Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [3] cIntensive Medicine Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [4] dInternal Medicine Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [5] eBiostatistics Clinic Unit, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [6] fMédical Oncology Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [7] gOral and Maxillofacial Surgery Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [8] hPharmacy Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                [9] iMicrobiology Department, Ramón y Cajal University Hospital, IRYCIS, Madrid, Spain
                Author notes
                Article
                ocl-0001
                10.1159/000525802
                9747739
                36063800
                73e9c6e3-1fe2-4da8-af1b-b0fe51617a3a
                Copyright © 2022 by S. Karger AG, Basel

                Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.

                History
                : 13 April 2022
                : 7 May 2022
                Page count
                Tables: 6, References: 36, Pages: 11
                Funding
                There was no funding support for this study.
                Categories
                Clinical Study

                sars-cov-2,cancer,oncologic treatments
                sars-cov-2, cancer, oncologic treatments

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