Clinical characteristics of COVID-19-infected cancer patients : a retrospective case study in three hospitals within Wuhan, China
Copyright © 2020 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved..
BACKGROUND: Cancer patients are regarded as a highly vulnerable group in the current Coronavirus Disease 2019 (COVID-19) pandemic. To date, the clinical characteristics of COVID-19-infected cancer patients remain largely unknown.
PATIENTS AND METHODS: In this retrospective cohort study, we included cancer patients with laboratory-confirmed COVID-19 from three designated hospitals in Wuhan, China. Clinical data were collected from medical records from 13 January 2020 to 26 February 2020. Univariate and multivariate analyses were carried out to assess the risk factors associated with severe events defined as a condition requiring admission to an intensive care unit, the use of mechanical ventilation, or death.
RESULTS: A total of 28 COVID-19-infected cancer patients were included; 17 (60.7%) patients were male. Median (interquartile range) age was 65.0 (56.0-70.0) years. Lung cancer was the most frequent cancer type (n = 7; 25.0%). Eight (28.6%) patients were suspected to have hospital-associated transmission. The following clinical features were shown in our cohort: fever (n = 23, 82.1%), dry cough (n = 22, 81%), and dyspnoea (n = 14, 50.0%), along with lymphopaenia (n = 23, 82.1%), high level of high-sensitivity C-reactive protein (n = 23, 82.1%), anaemia (n = 21, 75.0%), and hypoproteinaemia (n = 25, 89.3%). The common chest computed tomography (CT) findings were ground-glass opacity (n = 21, 75.0%) and patchy consolidation (n = 13, 46.3%). A total of 15 (53.6%) patients had severe events and the mortality rate was 28.6%. If the last antitumour treatment was within 14 days, it significantly increased the risk of developing severe events [hazard ratio (HR) = 4.079, 95% confidence interval (CI) 1.086-15.322, P = 0.037]. Furthermore, patchy consolidation on CT on admission was associated with a higher risk of developing severe events (HR = 5.438, 95% CI 1.498-19.748, P = 0.010).
CONCLUSIONS: Cancer patients show deteriorating conditions and poor outcomes from the COVID-19 infection. It is recommended that cancer patients receiving antitumour treatments should have vigorous screening for COVID-19 infection and should avoid treatments causing immunosuppression or have their dosages decreased in case of COVID-19 coinfection.
| Errataetall: |
CommentIn: Ann Oncol. 2020 Jul;31(7):838-839. - PMID 32243894 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:31 |
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| Enthalten in: |
Annals of oncology : official journal of the European Society for Medical Oncology - 31(2020), 7 vom: 01. Juli, Seite 894-901 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zhang, L [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 01.07.2020 Date Revised 21.06.2021 published: Print-Electronic CommentIn: Ann Oncol. 2020 Jul;31(7):838-839. - PMID 32243894 Citation Status MEDLINE |
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| doi: |
10.1016/j.annonc.2020.03.296 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM308098560 |
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| 100 | 1 | |a Zhang, L |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Clinical characteristics of COVID-19-infected cancer patients |b a retrospective case study in three hospitals within Wuhan, China |
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| 500 | |a Date Revised 21.06.2021 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a CommentIn: Ann Oncol. 2020 Jul;31(7):838-839. - PMID 32243894 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2020 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved. | ||
| 520 | |a BACKGROUND: Cancer patients are regarded as a highly vulnerable group in the current Coronavirus Disease 2019 (COVID-19) pandemic. To date, the clinical characteristics of COVID-19-infected cancer patients remain largely unknown | ||
| 520 | |a PATIENTS AND METHODS: In this retrospective cohort study, we included cancer patients with laboratory-confirmed COVID-19 from three designated hospitals in Wuhan, China. Clinical data were collected from medical records from 13 January 2020 to 26 February 2020. Univariate and multivariate analyses were carried out to assess the risk factors associated with severe events defined as a condition requiring admission to an intensive care unit, the use of mechanical ventilation, or death | ||
| 520 | |a RESULTS: A total of 28 COVID-19-infected cancer patients were included; 17 (60.7%) patients were male. Median (interquartile range) age was 65.0 (56.0-70.0) years. Lung cancer was the most frequent cancer type (n = 7; 25.0%). Eight (28.6%) patients were suspected to have hospital-associated transmission. The following clinical features were shown in our cohort: fever (n = 23, 82.1%), dry cough (n = 22, 81%), and dyspnoea (n = 14, 50.0%), along with lymphopaenia (n = 23, 82.1%), high level of high-sensitivity C-reactive protein (n = 23, 82.1%), anaemia (n = 21, 75.0%), and hypoproteinaemia (n = 25, 89.3%). The common chest computed tomography (CT) findings were ground-glass opacity (n = 21, 75.0%) and patchy consolidation (n = 13, 46.3%). A total of 15 (53.6%) patients had severe events and the mortality rate was 28.6%. If the last antitumour treatment was within 14 days, it significantly increased the risk of developing severe events [hazard ratio (HR) = 4.079, 95% confidence interval (CI) 1.086-15.322, P = 0.037]. Furthermore, patchy consolidation on CT on admission was associated with a higher risk of developing severe events (HR = 5.438, 95% CI 1.498-19.748, P = 0.010) | ||
| 520 | |a CONCLUSIONS: Cancer patients show deteriorating conditions and poor outcomes from the COVID-19 infection. It is recommended that cancer patients receiving antitumour treatments should have vigorous screening for COVID-19 infection and should avoid treatments causing immunosuppression or have their dosages decreased in case of COVID-19 coinfection | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a cancer | |
| 650 | 4 | |a retrospective case study | |
| 650 | 4 | |a severe clinical events | |
| 700 | 1 | |a Zhu, F |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, L |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, C |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, J |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, R |e verfasserin |4 aut | |
| 700 | 1 | |a Jia, P |e verfasserin |4 aut | |
| 700 | 1 | |a Guan, H Q |e verfasserin |4 aut | |
| 700 | 1 | |a Peng, L |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Y |e verfasserin |4 aut | |
| 700 | 1 | |a Peng, P |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, P |e verfasserin |4 aut | |
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| 700 | 1 | |a Shen, Q |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Y |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, S Y |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, J P |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, M |e verfasserin |4 aut | |
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