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      Differences in Outcomes and Factors Associated With Mortality Among Patients With SARS-CoV-2 Infection and Cancer Compared With Those Without Cancer : A Systematic Review and Meta-analysis

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      Author(s): , MRes 1 , 2 , , BSc, MSc, PhD 3 , , BSc 4 , 5 , , BSc, MBBS, PhD 6 , , MSc, BMBS, PhD 7 , 8 , , BSc, MBBS, PhD 1 , 9 ,
      Publication date (Electronic):
      Journal: JAMA Network Open
      Publisher: American Medical Association

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          Abstract

          This systematic review and meta-analysis analyzed the association of age, sex, and cancer types and therapies with survival rates among patients with both cancer and COVID-19 diagnosis.

          Key Points

          Question

          What are the clinical outcomes for patients with both cancer and SARS-CoV-2 infection?

          Findings

          In this systematic review and meta-analysis of 81 studies involving 61 532 patients with cancer, patients who were younger, had lung cancer, or had hematologic cancer were at an increased risk of mortality from COVID-19. Among anticancer treatments, chemotherapy was associated with the highest mortality risk and endocrine therapy was associated with the lowest risk.

          Meaning

          Findings of this study suggest that younger patients with cancer are a high-risk population for poor outcomes from COVID-19.

          Abstract

          Importance

          SARS-CoV-2 infection has been associated with more severe disease and death in patients with cancer. However, the implications of certain tumor types, treatments, and the age and sex of patients with cancer for the outcomes of COVID-19 remain unclear.

          Objective

          To assess the differences in clinical outcomes between patients with cancer and SARS-CoV-2 infection and patients without cancer but with SARS-CoV-2 infection, and to identify patients with cancer at particularly high risk for a poor outcome.

          Data Sources

          PubMed, Web of Science, and Scopus databases were searched for articles published in English until June 14, 2021. References in these articles were reviewed for additional studies.

          Study Selection

          All case-control or cohort studies were included that involved 10 or more patients with malignant disease and SARS-CoV-2 infection with or without a control group (defined as patients without cancer but with SARS-CoV-2 infection). Studies were excluded if they involved fewer than 10 patients, were conference papers or abstracts, were preprint reports, had no full text, or had data that could not be obtained from the corresponding author.

          Data Extraction and Synthesis

          Two investigators independently performed data extraction using the Preferred Reporting Items for Systematic Reviews and Meta-analyses ( PRISMA) reporting guideline. Meta-analysis was performed using a random-effects model.

          Main Outcomes and Measures

          The difference in mortality between patients with cancer and SARS-CoV-2 infection and control patients as well as the difference in outcomes for various tumor types and cancer treatments. Pooled case fatality rates, a random-effects model, and random-effects meta-regressions were used.

          Results

          A total of 81 studies were included, involving 61 532 patients with cancer. Among 58 849 patients with available data, 30 557 male individuals (52%) were included and median age ranged from 35 to 74 years. The relative risk (RR) of mortality from COVID-19 among patients with vs without cancer when age and sex were matched was 1.69 (95% CI, 1.46-1.95; P < .001; I 2 = 51.0%). The RR of mortality in patients with cancer vs control patients was associated with decreasing age (exp [b], 0.96; 95% CI, 0.92-0.99; P = .03). Compared with other cancers, lung cancer (RR, 1.68; 95% CI, 1.45-1.94; P < .001; I 2 = 32.9%), and hematologic cancer (RR, 1.42; 95% CI, 1.31-1.54; P < .001; I 2 = 6.8%) were associated with a higher risk of death. Although a higher point estimate was found for genitourinary cancer (RR, 1.11; 95% CI, 1.00-1.24; P = .06; I2 = 21.5%), the finding was not statistically significant. Breast cancer (RR, 0.51; 95% CI, 0.36-0.71; P < .001; I 2 = 86.2%) and gynecological cancer (RR, 0.76; 95% CI, 0.62-0.93; P = .009; I 2 = 0%) were associated with a lower risk of death. Chemotherapy was associated with the highest overall pooled case fatality rate of 30% (95% CI, 25%-36%; I 2 = 86.97%; range, 10%-100%), and endocrine therapy was associated with the lowest at 11% (95% CI, 6%-16%; I 2 = 70.68%; range, 0%-27%).

          Conclusions and Relevance

          Results of this study suggest that patients with cancer and SARS-CoV-2 infection had a higher risk of death than patients without cancer. Younger age, lung cancer, and hematologic cancer were also risk factors associated with poor outcomes from COVID-19.

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          Most cited references108

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

          David Moher, Alessandro Liberati, Jennifer Tetzlaff … (2011)
          David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
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            Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China

            Wenhua Liang, Weijie Guan, Ruchong Chen … (2020)
            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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              Comorbidity and its impact on 1590 patients with Covid-19 in China: A Nationwide Analysis

              Wei-jie Guan, Wen-hua Liang, Yi. Zhao … (2020)
              Background The coronavirus disease 2019 (Covid-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with coronavirus disease 2019 (Covid-19) by stratifying the comorbidity status. Methods We analysed the data from 1590 laboratory-confirmed hospitalised patients 575 hospitals in 31 province/autonomous regions/provincial municipalities across mainland China between December 11th, 2019 and January 31st, 2020. We analyse the composite endpoints, which consisted of admission to intensive care unit, or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared according to the presence and number of comorbidities. Results The mean age was 48.9 years. 686 patients (42.7%) were females. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD [hazards ratio (HR) 2.681, 95% confidence interval (95%CI) 1.424–5.048], diabetes (HR 1.59, 95%CI 1.03–2.45), hypertension (HR 1.58, 95%CI 1.07–2.32) and malignancy (HR 3.50, 95%CI 1.60–7.64) were risk factors of reaching to the composite endpoints. The HR was 1.79 (95%CI 1.16–2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61–4.17) among patients with two or more comorbidities. Conclusion Among laboratory-confirmed cases of Covid-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.
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                Author and article information

                Journal
                Journal ID (nlm-ta): JAMA Netw Open
                Journal ID (iso-abbrev): JAMA Netw Open
                Title: JAMA Network Open
                Publisher: American Medical Association
                ISSN (Electronic): 2574-3805
                Publication date (Electronic): 9 May 2022
                Publication date Collection: May 2022
                Publication date PMC-release: 9 May 2022
                Volume: 5
                Issue: 5
                Electronic Location Identifier: e2210880
                Affiliations
                [1 ]Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Institute of Translational Medicine, Liverpool, United Kingdom
                [2 ]University of Liverpool, School of Medicine, Liverpool, United Kingdom
                [3 ]Department of Health Data Science, Institute of Population Health, University of Liverpool, United Kingdom
                [4 ]Department of Political Science and School of Public Policy, University College London, London, United Kingdom
                [5 ]Department of Political Science, University of Copenhagen, Copenhagen, Denmark
                [6 ]Tropical and Infectious Disease Unit, Liverpool University Hospitals National Health Service (NHS) Foundation Trust, Member of Liverpool Health Partners, Liverpool, United Kingdom
                [7 ]Department of Clinical Infection Microbiology and Immunology, Department of Clinical Infection, University of Liverpool, Liverpool, United Kingdom
                [8 ]University of Liverpool Institute of Infection and Global Health, Veterinary and Ecological Sciences, Liverpool, United Kingdom
                [9 ]The Clatterbridge Cancer Centre NHS Foundation Trust, Liverpool, United Kingdom
                Author notes
                Article Information
                Accepted for Publication: March 21, 2022.
                Published: May 9, 2022. doi:10.1001/jamanetworkopen.2022.10880
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Khoury E et al. JAMA Network Open.
                Corresponding Author: Carlo Palmieri, BSc, MBBS, PhD, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Sherrington Building, Ashton Street, Liverpool, L69 3GE, United Kingdom ( c.palmieri@ 123456liverpool.ac.uk ).
                Author Contributions: Ms Khoury had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Khoury, Turtle, Palmieri.
                Acquisition, analysis, or interpretation of data: Khoury, Nevitt, Rohde Madsen, Davies, Palmieri.
                Drafting of the manuscript: Khoury, Rohde Madsen, Turtle, Palmieri.
                Critical revision of the manuscript for important intellectual content: Khoury, Nevitt, Turtle, Davies, Palmieri.
                Statistical analysis: Nevitt, Rohde Madsen, Davies.
                Administrative, technical, or material support: Khoury.
                Supervision: Nevitt, Turtle, Palmieri.
                Conflict of Interest Disclosures: Dr Turtle reported receiving personal fees paid to the University of Liverpool from Eisai Ltd. Dr Palmieri reported receiving grants from Pfizer and Daiichi Sankyo as well as personal fees from Pfizer, Roche, Daiichi Sankyo, Novartis, Exact Sciences, Gilead, SeaGen, and Eli Lilly outside the submitted work. No other disclosures were reported.
                Funding/Support: Dr Palmieri and Dr Turtle were supported by grant MR/V028979/1 from UK Research Innovation-Department for Health and Social Care COVID-19 Rapid Response Rolling Call. Dr Palmieri was supported by grant C18616/A25153 from the Liverpool Experimental Cancer Medicine Centre, by Cancer Research UK, and by the Clatterbridge Cancer Charity and North West Cancer. Ms Khoury was supported by award CR1054 from North West Cancer Research Fund to support a Master of Research. Dr Turtle was supported by contract 75F40120C00085 from the US Food and Drug Administration Medical Countermeasures Initiative, by fellowship 205228/Z/16/Z from the Wellcome Trust, and by grant NIHR200907 from the National Institute for Health Research (NIHR) Health Protection Research Unit in Emerging and Zoonotic Infections at the University of Liverpool in partnership with Public Health England, in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.
                Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Disclaimer: The views expressed herein are those of the authors and do not reflect the official policy or position of the National Health Service, the NIHR, the Department of Health, or Public Health England.
                Article
                Publisher ID: zoi220329
                DOI: 10.1001/jamanetworkopen.2022.10880
                PMC ID: 9086843
                PubMed ID: 35532936
                SO-VID: 6c737566-35f5-403d-b705-7f0bf01eeda9
                Copyright © Copyright 2022 Khoury E et al. JAMA Network Open.
                License:

                This is an open access article distributed under the terms of the CC-BY License.

                History
                Date received : 11 January 2022
                Date accepted : 21 March 2022
                Categories
                Subject: Research
                Subject: Original Investigation
                Subject: Online Only
                Subject: Oncology

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