Evidence map›Paper›PMID 33287747›Full record

ArticleBMC cancer2020

Cancer patient management strategy in a Cancer Center of Zhejiang, China during the COVID-19 pandemic.

Songxiao Xu, Xiangdong Cheng, Zhiwen Pan, Qian Song, Yihong Wang, Juan Xiong, Yongyi Chen, Fan Fan, Jing Zhu, Wanying Wu and 10 more

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Cancer Patients during COVID-19 Pandemic: A Mini-Review.Healthcare (Basel, Switzerland) · 2023
    Review
  2. Article
  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 5 institutions in 1 country.

Songxiao XuDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Xiangdong ChengInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Zhiwen PanDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Qian SongDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Yihong WangDepartment of Pathology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Juan XiongDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Yongyi ChenDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Fan FanDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Jing ZhuDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Wanying WuInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Xueying DengInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Yanpin YuInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Xiaohong XuDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Wenhu ChenDepartment of Clinical Laboratory, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Tao ZhuInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Yang YuInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Kaizhong LiuInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Guoliang ShaoInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
Ming ChenInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China. chenming@zjcc.org.cn.
Enyan YuInstitute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China. yuenyan@aliyun.com.
Chinese Academy of Sciences · CNUniversity of Chinese Academy of Sciences · CNZhejiang Cancer Hospital · CNCancer Hospital of Chinese Academy of Medical Sciences · CNSir Run Run Shaw Hospital · CN

Funding

Natural Science Foundation of Zhejiang Province LY21H200001the fifth-level talent introduction research start-up grant from Zhejiang Cancer Hospital N/A
6 · The paper itself

Abstract

backgroundDue to the increased risk of viral infection and the severe shortage of medical resources during the pandemic of COVID-19, most hospitals in the epidemic areas significantly reduced non-emergency admissions and services, if not closed. As a result, it has been difficult to treat cancer patients on time, which adversely affects their prognosis. To address this problem, cancer centers must develop a strategic plan to manage both inpatients and outpatients during the pandemic, provide them with the necessary treatment, and at the same time prevent the spread of the virus among patients, visitors and medical staff.

methodsBased upon the epidemic situation in Zhejiang Province, China, the number of running non-emergency medical wards in the Zhejiang Cancer Hospital was gradually increased in a controlled manner. All staff of the hospital received COVID-19 preventive training and was provided with three different levels of protection according to the risks of their services. Only patients without a known history of SARS-CoV-2 contact were eligible to schedule an appointment. Body temperature was measured on all patients upon their arrival at the hospital. Chest CT image, blood cell counting and travel/contact history were investigated in patients with fever. Respiratory tract samples, such as sputum and throat swabs, from all patients, including those clinically suspected of SARS-CoV-2 infection, were collected for nucleic acid detection of SARS-CoV-2 before treatment.

resultsA total of 3697 inpatients and 416 outpatients seeking cancer treatment were enrolled from February 1 to April 3, 2020, in compliance with the hospital's infection-control interventions. The clinicopathological parameters of the patients were summarized herein. 4237 samples from 4101 patients produced negative RNA testing results. Four clinically suspected patients all presented negative RNA test results and were excluded from the SARS-CoV-2 infection through follow-up retesting and monitoring. Seven patients with only N-gene positive results were retested, followed by CT scan and SARS-CoV-2 contact history investigation. All of them were finally diagnosed as non-infected patients. There was one outpatient who was confirmed positive by virus RNA test and then followed up. She might be an asymptomatic laboratory-confirmed case. During the study period, there was no SARS-CoV-2 infection among staff, patients and escorts of patients in the Zhejiang Cancer Hospital.

conclusionThis study suggested our infection-control interventions, including viral nucleic acid test, could be used as a reliable method to screen cancer patients in the area with moderate COVID-19 prevalence. Cancer may not be a high-risk factor of SARS-CoV-2 infection.

Indexed as

Disease ManagementPandemicsAdolescentAdultChinaCOVID-19FemaleHumansMaleMiddle AgedNeoplasmsPatientsYoung AdultCancerCOVID-19Infection-control interventions

Identifiers

PMID33287747
PMCPMC7719731
OpenAlexW3113167078

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.