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Impact of cancer on mortality and severity of corona virus disease 2019

Authors :
Yingying Kang
Yi Zhang
Yunling Tian
Lina Xing
Hao Han
Dairong Xie
Ruinian Zhang
Jing Dong
Rongna Lian
Yage Yu
Source :
Medicine
Publication Year :
2020
Publisher :
Ovid Technologies (Wolters Kluwer Health), 2020.

Abstract

Background: Cancer patients are in a state of systemic immunosuppression and are considered a highly vulnerable population in the Corona Virus Disease 2019 (COVID-19) epidemic. However, the relationship between cancer and the severity and mortality of patients with COVID-19 remains unclear. This study aims to evaluate whether cancer patients with COVID-19 may be at an increased risk of severe illness and mortality. Methods: We will perform comprehensive searches in PubMed, EMBASE.com, Web of Science, and the Cochrane Central Register of Controlled Trials to identify studies providing prevalence of cancer between patients with severe and non-severe illness or between non-survivors and survivors. We will use the Newcastle-Ottawa quality assessment scale to assess the quality of included studies. We will conduct pairwise meta-analyses to compute the odds ratio and 95% confidence interval using the Mantel Haenszel method with the random-effects model. The statistical heterogeneity will be assessed using the I2 statistic. Subgroup analyses, sensitivity analyses, and meta-regression analyses will be performed to explore the sources of heterogeneity. Results: The results of this study will be published in a peer-reviewed journal. Conclusion: Our meta-analysis will systematically evaluate the association between cancer and the severity and mortality of patients with COVID-19. This study will provide evidence to help determine whether cancer patients should be provided with special precautions and advised to use stronger personal protection. INPLASY registration number: INPLASY202090093.

Details

ISSN :
15365964 and 00257974
Volume :
99
Database :
OpenAIRE
Journal :
Medicine
Accession number :
edsair.doi.dedup.....1a6c1385e0dd398e123050dcd31c23bf