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      Reactions and countermeasures of medical oncologists towards the incoming COVID-19 pandemic: a WhatsApp messenger-based report from the Italian College of Chief Medical Oncologists

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          Abstract

          Background

          This descriptive, unplanned investigation has been undertaken to report reactions, attitudes and countermeasures which have been put in place and implemented by medical oncology units facing the COVID-19 outbreak in Southern Italy.

          Materials and methods

          Data have been retrospectively obtained from the time-related analysis of conversations via a WhatsApp messenger-based group chat between the medical directors belonging to the Italian College of Medical Oncology Directors. Overall number, intensity and time trend of conversations related to reactions during the 4 weeks of observation related to the crucial events which occurred between 24 February and 28 March, 2020 2020 are included. A sentiment analysis of conversations was also carried out.

          Results

          We report 956 conversations among 19 medical oncology units related to reactions to the crucial events, such as epidemic spread, Government ordinances and guidelines during the 4 weeks of observation. Data show significant awareness of problems linked to the COVID-19 spread among oncologists and rapid diffusion of countermeasures. Actions taken were correlated time wise to crucial events. A correlation between conversations and the volume of activity of oncology units was found. By analysing the sentiment analysis of raw data, positive emotions were reduced in percentage over the weeks. A significant increase in negative emotions was observed as the outbreak impacted on the healthcare system.

          Conclusion

          In our experience, the WhatsApp instant-messaging system seems to be a useful tool to share news and reactions between medical oncologists to rapidly implement necessary health measures and answers to most cancer patients’ needs and queries in the COVID-19 pandemic scenario.

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          Most cited references25

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

            Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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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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                Author and article information

                Journal
                Ecancermedicalscience
                Ecancermedicalscience
                ecancermedicalscience
                ecancermedicalscience
                Cancer Intelligence
                1754-6605
                2020
                15 May 2020
                : 14
                : 1046
                Affiliations
                [1 ]Medical Oncology Unit, Arnas, Ospedale Civico, Palermo, 90100, and National President of CIPOMO, Italy
                [2 ]Medical Oncology Unit, Arnas, Ospedale Garibaldi, Catania, 95100, Italy
                [3 ]Medical Oncology Unit, Ospedale Buccheri La Ferla, Palermo, 90100, Italy
                [4 ]Medical Oncology Unit, Ospedale San Giovanni di Dio, Agrigento, 92100, Italy
                [5 ]Medical Oncology Unit, Istituto Clinico Humanitas, Catania, 95100, Italy
                [6 ]Medical Oncology Unit, Ospedale Paterno Arezzo, Ragusa, 97100, Italy
                [7 ]Medical Oncology Unit, Ospedale Vittorio Emanuele, Castelvetrano, 91022, Italy
                [8 ]Medical Oncology Unit, Ospedale San Vincenzo, Taormina, 98039, Italy
                [9 ]Medical Oncology Unit, Istituto Oncologico Mediterraneo, Viagrande, 95029, Italy
                [10 ]Medical Oncology Unit, Policlinico, Catania, 95100, Italy
                [11 ]Medical Oncology Unit, Ospedale Giglio, Cefalù, 90015, Italy
                [12 ]Medical Oncology Unit, Ospedale Umberto I, Siracusa, 96100, Italy
                [13 ]Medical Oncology Unit, Ospedale Vittorio Emanuele, Gela, 93012, Italy
                [14 ]Medical Oncology Unit, Ospedale Cervello-Villa Sofia, Palermo, 90100, Italy
                [15 ]Medical Oncology Unit, Ospedale Sant’Elia, Caltanissetta, 93100, Italy
                [16 ]Medical Oncology Unit, Ospedale San Antonio Abate, Trapani, 91100, Italy
                [17 ]GSTU Foundation, Palermo, 90100, Italy
                [18 ]Risk Management Unit, Policlinico, Palermo, 90100, Italy
                [19 ]Medical Oncology Unit, Ospedale La Maddalena, University of Palermo, Palermo, 90100, Italy
                Author notes
                Correspondence to: Vittorio Gebbia vittorio.gebbia@ 123456gmail.com
                Article
                can-14-1046
                10.3332/ecancer.2020.1046
                7289620
                593590e5-14e7-471b-88b8-0cb912d40035
                © the authors; licensee ecancermedicalscience.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 April 2020
                Categories
                Research

                Oncology & Radiotherapy
                whatsapp messenger,medical oncologists,reactions,action taken,covid-19 outbreak,sentimental analysis

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