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      Effect of radiotherapy interruption due to COVID-19 outbreak

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          Abstract

          To the Editor The impact of the COVID-19 pandemic on cancer death was reported recently[1].Wuhan where COVID-19 broke out has been critically hit[2], [3]. The emergence has affected every aspect of health care, including the delivery of standard radiotherapy to patients with cancer. Those patients was facing disruption because of concerns about their susceptibility to the serious risks of COVID-19, travel restrictions, and the shortage of personnel, beds and personal protective equipment, and it has been reported that many cancer patients in hospitals of Wuhan got into such difficulties, so the number of patients receiving radiotherapy significantly decreased during the pandemic.[4], [5] The radiotherapy center of Renmin Hospital of Wuhan University (RHWU) was shut down on January 24, and reopened until March 9, 2020.Thus, many patients were unplanned interrupted of radiotherapy during this period. Our survey of 140 consecutive patients in RHWU from March 9 to June 30, 2020, summarizes the clinical characteristics and outcome of these patients whose radiotherapy interrupted for 45 days or longer. The median age at diagnosis was 57 (range 27–83) years,70 patients (50%) were men, and 70 (50%) were women. Including lung(n = 26[18.6%]), breast(n = 21[15%]), head and neck cancer (n = 24[17.1%]), or gastrointestinal (n = 25[17.9%])or gynecological cancer (n = 17[12.1%]). During the pandemic, 76 patients stayed at home without any cancer treatments. Twenty-six patients took traditional Chinese medicine, 12 took oral chemotherapy or molecular targeted therapy medications, 10 continued radiotherapy in other hospitals. 87 (62.1%) patients have returned to our center. The result indicated that stage IV was associated with poor prognosis compared with stage I-III. But the delivered radiation dose was not associated with disease prognosis (Table1 ).After 5 months of follow-up, 16 patients including nine females and seven males were died (11.4%), age from 40 to 77 years old. 11 were diagnosed with stage IV cancer and five with stage III cancer. 14 (10.0%) died of cancer and 2 (1.4%) died of COVID-19. Table 1 Characteristics of patients with interrupted radiotherapy* No. Tumor TNM stage PD SD PR P IV 17 13 1 0.000** III 6 14 4 II 1 20 3 I 0 7 1 Radiation dose delivered/prescribed (radical radiotherapy) >=50% 4 12 5 0.153 <50% 6 10 2 Aim of radiotherapy Palliative 9 4 0 /# Radical 10 22 7 Postoperative 5 28 1 Preoperative 0 0 1 Site of primary cancer Intracranial 4 6 1 /# Head and neck 4 11 4 Chest 11 23 3 Abdomen 1 1 0 Pelvic cavity 2 9 1 Others 2 4 0 List of abbreviations:PD: progressive disease; SD: stable disease; PR: partial response. * Only including the 87 patients who came back to our hospital to continue therapy. ** Stage I, II, III were compared as a whole group with stage IV. # P value was not calculated as sample size is too small for statistical analyze. Suboptimal delivery of radiotherapy (including delays, interruptions or omissions) has been demonstrated to compromise both local control and survival, especially for stage IV cancer patients. Other anti-tumor therapies (oral chemotherapy, endocrinotherapy or molecular targeted therapy) maybe improve the situation. Salvage radiotherapy was practicable, such as weekend treatments or increased number of daily fractions; increased dose per fraction; delivering extra fractions[6]. Balancing the risks of infection and subsequent mortality with the increased risks of cancer mortality derived from delaying treatment is of utmost importance,to date,many cancer centers have shared their strategies and experiences,which were effective in protecting the patient and staff from infection.[7], [8], [9] Further follow-up may clearly demonstrate the consequence of treatment interruption on local control and survival of cancer patients. Author Contributions Drs Li and Song had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. They are co-senior authors. Drs Yu and Hu are co-first authors who contributed equally to this work.

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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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            Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

            Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
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              Is Open Access

              The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study

              Summary Background Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types. Methods In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15–84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data. Findings We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9–9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266–295) and 344 (329–358) additional deaths. For colorectal cancer, we estimate 1445 (1392–1591) to 1563 (1534–1592) additional deaths, a 15·3–16·6% increase; for lung cancer, 1235 (1220–1254) to 1372 (1343–1401) additional deaths, a 4·8–5·3% increase; and for oesophageal cancer, 330 (324–335) to 342 (336–348) additional deaths, 5·8–6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291–3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204–63 229 years. Interpretation Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer. Funding UK Research and Innovation Economic and Social Research Council.
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                Author and article information

                Journal
                Radiother Oncol
                Radiother Oncol
                Radiotherapy and Oncology
                Published by Elsevier B.V.
                0167-8140
                1879-0887
                11 October 2020
                11 October 2020
                Affiliations
                Department of Oncology, Renmin Hospital of Wuhan University, 238 Jiefang Rd, Wuhan 430060, China
                Author notes
                [* ]Corresponding authors.
                Article
                S0167-8140(20)30830-6
                10.1016/j.radonc.2020.09.055
                7548113
                33053379
                f86a4bc5-0831-41e0-ae1d-2041bc93c9d9
                © 2020 Published by Elsevier B.V.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 15 September 2020
                : 20 September 2020
                : 27 September 2020
                Categories
                COVID-19 Rapid Letter

                Oncology & Radiotherapy
                covid-19,radiotherapy,interruption
                Oncology & Radiotherapy
                covid-19, radiotherapy, interruption

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