key: cord-0987905-ezsqwm4t authors: Tian, Yehong; Qiu, Xiaowei; Wang, Chengxiang; Zhao, Jianxin; Jiang, Xin; Niu, Wenquan; Huang, Jinchang; Zhang, Fengyu title: Cancer associates with risk and severe events of COVID‐19: A systematic review and meta‐analysis date: 2020-07-19 journal: Int J Cancer DOI: 10.1002/ijc.33213 sha: b7e871f467c7e9e8b922f90e0ce27cccb5c239da doc_id: 987905 cord_uid: ezsqwm4t Evidence is mounting to indicate that cancer patients may have more likelihood of having coronavirus disease 2019 (COVID‐19) but lack consistency. A robust estimate is urgently needed to convey appropriate information to the society and the public, in the time of ongoing COVID‐19 pandemic. We performed a systematic review and meta‐analysis through a comprehensive literature search in major databases in English and Chinese, and two investigators conducted publication selection and data extraction independently. A meta‐analysis was used to obtain estimates of pooled prevalence of cancer in patients with COVID‐19 and determine the association of cancer with severe events, after assessment of potential heterogeneity, publication bias, and correction for the estimates when necessary. Total 38 studies comprising 7,094 patients with COVID‐9 were included; the pooled prevalence of cancer was estimated at 2.3% (95% confidence limit[CL] [0.018, 0.029]; p<0.001) overall and 3.2% (95% CL [0.023,0.041]; p<0.001) in Hubei province; the corresponding estimates were 1.4% and 1.9% after correction for publication bias; cancer was significantly associated with the events of severe cases (odds ratio [OR]=2.20, 95% CL[1.53, 3.17]; p<0.001) and death (OR=2.97, 95% CL[1.48, 5.96]; p=0.002) in patients with COVID‐19, there was no significant heterogeneity and a minimal publication bias. We conclude that cancer comorbidity is associated with the risk and severe events of COVID‐19; special measures should be taken for individuals with cancer. This article is protected by copyright. All rights reserved. Coronavirus disease 2019 is a new respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 1 Because the causative viral pathogen is highly infective and with human-to-human transmission, the COVOD-19 is having a fast spread worldwide. On March 12, 2020 , when there were over 20,000 confirmed cases and 1,000 deaths in the European region, the World Health Organization (WHO) announced a pandemic of COVID-19, which has caused the ongoing global public health emergency. COVID-19 is an infectious disease and almost all people lack specific immunity to the novel coronavirus. Individuals can be infected by contact with respiratory droplets containing SARS-CoV-2 virus or the surfaces contaminated. 2 Older people and individuals with underlying chronic health conditions may increase the risk of developing COVID-19 and being with severe events, likely due to the aging-associated dysregulation of immune systems. 3 The major symptoms of clinical manifestation include fever, cough, fatigue, myalgia or arthralgia, sore throat, headache, shortness of breath (anhelation or dyspnea), and sputum production. 4 A clinical report from one of the hospitals in Wuhan shows that patients who received Intensive Care Unit (ICU) services are more prevalent of respiratory failure (61.1%), arrhythmia (44.4%) , and a sudden shock (30.6%). 5 In some severe cases, the coronavirus infection can lead to acute respiratory distress syndrome, acute cardiac or kidney injury, secondary infection, shock, and high risk of death. 6 A nationwide report (n=72,314) from China shows that the severe and critical cases of COVID-19 account for 19% and the case-fatality rate is about 49.0% in the critical cases 7 because of lacking effective treatment for the coronavirus 8 . In addition, multiple reports have shown that underlying chronic health conditions such as hypertension and diabetes are associated with severe patients with 9 This is likely because the receptor of angiotensin-converting enzyme-2 (ACE-2), which the spike proteins of the pathogen SARS-CoV-2 bind to enter the host cells, is associated with hypertension 10 and diabetes 11 . Also, there is a growing interest in the association of cancer with 12 Cancer is a severe underlying condition in patients with COVID-19. Patients with cancer are usually characterized by older age, compromised immune systems, and comorbid with chronic diseases, which might be partially caused by antitumor treatment. Individuals with cancer may be more likely to have COVID-19. One hospital-based study has noted a few cases with cancer, 13 but a robust estimate of cancer prevalence in patients with COVID-19 is lacking. Here, we conducted a systematic review and meta-analysis of cancer prevalence in patients with COVID-19, and examined the association of cancer with severe events, which include severe cases judged by clinical symptoms (SJCS), utilization of ICU services, and death. The meta-analysis was conducted in accordance with the guidelines in the Preferred Reporting Items for Systematic Reviews and Meta-analyzes (PRISMA) statement. 14 This article is protected by copyright. All rights reserved. Conducting of this systematic review and meta-analysis was based on existing literature, and therefore was not registered. A literature search was first performed in major databases of PubMed, Elsevier, and Web of Science to identify all published studies with full text, as of April 23, 2020, and the language was first limited to English. The search terms were as follows: "2019-nCoV" [All fields] or "novel coronavirus" [All fields] or "SARS-CoV-2" [All fields] or "COVID-19" [All fields]. Additional search was performed in the three major Chinese databases ─ China National Knowledge Infrastructure (CNKI) (https://www.cnki.net), WanFang (http://www.wanfangdata.com.cn), and VIP (http://www.cqvip.com). The above process was performed by two investigators (Y. T., and X. Q.) independently. A study was included when met all the following criteria: 1) reporting information on clinical characteristics and epidemiology of the patients with a laboratory-confirmed diagnosis of COVID-19, 2) containing information on cancer and clinical subtypes, or outcomes of the clinically validated death, severe cases, ICU care, or disease progression, and 3) an original study. A study was included when met one of the following criteria: 1) case report, animal research, review, guideline, expert consensus, letter, protocol, news, or comment, 2) with incomplete information on related data, 3) only on special populations such as children, pregnancy, older people, or 4) sample size of fewer than 20 individuals and overlapped study samples. Also, we excluded two studies that were conducted in the populations of the United Studies and Iran. Two investigators (X. J. and X. Q.) screened and extracted data according to the predesigned form of Excel spreadsheet independently. Questions or inconsistencies were resolved through discussion or consultation with a third expert (J. H.) to make a final decision. Information extracted from the included literature includes the name of the first author, year of publication, region, sample size, age, gender, the status of severe cases, utilization of ICU, and event of death, where appropriate. The Stata (special edition version 14.0) for Windows (Stata Corp, College Station, Texas) was used to obtain the estimates of cancer prevalence in patients with COVID-19. A pooled odds ratio (OR) was used to measure the strength of association, and 95% confidence limit (CL) measured the precision of the estimates. Heterogeneity was measured by , a statistic that measures the proportion of variance in the estimates is due to the heterogeneity between studies, where Q is Cochran's statistic, a classical measure of heterogeneity, which can provide a statistical test based on Chi-square statistic. 15 A threshold of p-value was set at 0.05. In the presence of a significant heterogeneity, a random-effect meta-analysis was performed. Also, cumulative meta-analysis, sensitivity analysis, subgroup analysis This article is protected by copyright. All rights reserved. was performed to assess the systematic bias, and meta-regression modeling was performed to adjust for potential covariates. Publications bias was assessed using the Begg's rank correlation test and Egger's linear regression test. A threshold of p-value was set at 0.05. In the presence of publication bias, "trim and fill" method was used to estimate the number of expected missing studies and to obtain a corrected estimate. 16 Study power was calculated using PS (Power and Sample Size Calculations, version 3.0) software. Through a comprehensive literature search, 5,724 relevant articles were identified. Duplications were found by carefully scanning the titles and abstracts, and then Table 1 . The pooled prevalence of cancer in patients with COVID-19 ( Figure 1 ) was estimated at 2.3% (95% CL [0.018, 0.029]; I 2 =52.6%, p<0.001), which was obtained with a random-effect meta-analysis. Cumulative analysis showed the estimates of early This article is protected by copyright. All rights reserved. studies were fluctuating and with larger variance. However, by the last few studies, the estimates and precision approached a constant (Supplementary Figure 1) . Hubei (Figure 2 ) was at 3.2% (95% CL [0.023, 0.041]; I 2 =59.3%; p<0.001) with a random-effect meta-analysis, while it was at 1.0% in the samples outside Hubei and 1.8% in the samples from multiple provinces. To determine additional source of heterogeneity in the studies, we performed a sensitivity and subgroup analysis. Sensitivity analysis showed the effect size had no noted deviation when an individual study was omitted at a time (Supplementary Figure 2 ). Subgroup analysis indicated that the estimates were not significantly different by gender and sample size, but were affected by age and sample location ( Table 2) . Meta-regression analyses showed that the cancer prevalence in patients with COVID-19 was significantly affected by sample location (p=0.016), but not gender (p=0.403), age (p=0.257), and sample size (p=0.740), which were also confirmed by multiple meta-regression analysis that only sample location (p=0.036) was a significant factor causing the overall heterogeneity, supporting our analysis performed above by Hubei-only. Seventeen studies, including eleven of which were from Hubei province, reported the information on severe cases defined by clinical symptoms and ICU experience. No This article is protected by copyright. All rights reserved. significant heterogeneity (I 2 =19.2%; p=0.230) was presented between the studies (Figure 3a) . A fixed-effect meta-analysis showed that cancer was significantly associated with the severe cases of COVID-19 (OR=2.20, 95% CL [1.53, 3.17] ; p<0.001). The power to detect this significant association was estimated to be 85.9%. In addition, eight studies reported the outcome of death, and all were from Hubei province. No heterogeneity (I 2 =0%, p=0.447) was observed (Figure 3b) . A fixed-effect meta-analysis showed that cancer was associated with the risk of death (OR=2.97, 95% CL [1.48, 5.96 ]; p=0.002) in patients with COVID-19, with the estimated power to detect this association at 80.1%. Assessment of publication bias is a crucial step to present the findings from a meta-analysis objectively. We noted a significant (p<0.01) publication bias in the meta-analysis of 38 studies; correction for the publication bias was made with the "filled" studies for overall sample (Figure 4a ) and Hubei-only (Figure 4b) , separately. The random-effect meta-analysis was then used to obtain an adjusted estimate of (Figure 4c and 4d) , and no evidence for a significant publication bias (p>0.5, n=17) in the association of cancer with the severe cases, either. To the best of our knowledge, this is a more comprehensive meta-analysis that has investigated the association between cancer with COVID-19 so far. This article is protected by copyright. All rights reserved. However, we observed a noted regional difference in the cancer prevalence, which is likely due to the chance of exposure. and adequate personal protection equipment to avoid effective exposure to the pathogens. It is expected that individuals with cancer, later outside Hubei, may have taken more careful protection from being exposed. This is supported by a significant regional difference in other comorbid conditions such as hypertension ( However, the mechanism underlying the association of cancer with severe events of COVID-19 seem more complicated without a rigorous study. A pathological study of a single individual with COVID-19 indicates that inflammation and cytokines-associated lung injury may be associated with severe events of This observation is supported by an analysis of more clinical samples that severe events or death of COVID-19 are significantly associated with an increase in innate immune cells such as neutrophils and inflammatory cytokines, and lymphopenia, 29, 52 indicating immunopathology is involved. However, people argue that the "cytokine storm" seems not to explain the association of cancer with the severe event of COVID-19, 62 as the development of cancer is caused by blunted immune status such as immunosuppression; 63 and also, a case report showed that immunosuppression might be with favorable outcomes in cancer patients with This article is protected by copyright. All rights reserved. The study has limitations. First, most of the included studies were based on hospital-based case-series, selection bias may exist and affect the estimates, although the publication bias was assessed and corrected. Second, due to limited clinical information, we were unable to perform the study by the site of cancer. Lastly, while we had carefully investigated all articles, the included studies were limited to the study samples in China to reduce the heterogeneity. Even though two studies in non-Chinese populations met our criteria for inclusion and exclusion, one from Iran and one from the United States of American, they reported two extreme cases of cancer prevalence in patients with COVID-19; they were excluded from the analysis as outliers. 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