key: cord-266935-bkan3mwy
authors: Giannakoulis, Vassilis G.; Papoutsi, Eleni; Siempos, Ilias I.
title: Effect of Cancer on Clinical Outcomes of Patients With COVID-19: A Meta-Analysis of Patient Data
date: 2020-06-08
journal: JCO Glob Oncol
DOI: 10.1200/go.20.00225
sha: 
doc_id: 266935
cord_uid: bkan3mwy

PURPOSE: Whether cancer is associated with worse prognosis among patients with COVID-19 is unknown. We aimed to quantify the effect (if any) of the presence as opposed to absence of cancer on important clinical outcomes of patients with COVID-19 by carrying out a systematic review and meta-analysis. METHODS: We systematically searched PubMed, medRxiv, COVID-19 Open Research Dataset (CORD-19), and references of relevant articles up to April 27, 2020, to identify observational studies comparing patients with versus without cancer infected with COVID-19 and to report on mortality and/or need for admission to the intensive care unit (ICU). We calculated pooled risk ratios (RR) and 95% CIs with a random-effects model. The meta-analysis was registered with PROSPERO (CRD42020181531). RESULTS: A total of 32 studies involving 46,499 patients (1,776 patients with cancer) with COVID-19 from Asia, Europe, and the United States were included. All-cause mortality was higher in patients with versus those without cancer (2,034 deaths; RR, 1.66; 95% CI, 1.33 to 2.07; P < .0001; 8 studies with 37,807 patients). The need for ICU admission was also more likely in patients with versus without cancer (3,220 events; RR, 1.56; 95% CI, 1.31 to 1.87; P < .0001; 26 studies with 15,375 patients). However, in a prespecified subgroup analysis of patients > 65 years of age, all-cause mortality was comparable between those with versus without cancer (915 deaths; RR, 1.06; 95% CI, 0.79 to 1.41; P = .71; 8 studies with 5,438 patients). CONCLUSION: The synthesized evidence suggests that cancer is associated with worse clinical outcomes among patients with COVID-19. However, elderly patients with cancer may not be at increased risk of death when infected with COVID-19. These findings may inform discussions of clinicians with patients about prognosis and may guide health policies.

An ever-increasing number of people in the global population are suffering from cancer. 1 Patients with cancer are therefore anticipated to be affected during the current epidemic of COVID-19. However, whether, when infected with COVID-19, patients with versus without cancer are at increased risk for unfavorable clinical outcomes is unknown. This was highlighted in a plenary session at the American Association for Cancer Research Virtual Annual Meeting held on April 27-28, which subsequently issued a call for relevant research. 2 We therefore aimed to quantify the effect (if any) of the presence as opposed to absence of cancer on important clinical outcomes, such as mortality and need for admission in the intensive care unit (ICU), of patients with COVID-19 by carrying out a systematic review and meta-analysis.

We reported the current systematic review and metaanalysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. 3 We prespecified inclusion criteria, methods of data synthesis, and outcomes in a protocol registered in PROSPERO (CRD42020181531) and available online

We considered observational cohort studies of COVID-19, which reported on all-cause mortality and/or need for ICU admission of patients with cancer versus patients without cancer. Details on the assessment of need for ICU admission are provided in the Data Supplement. Both peer-reviewed papers and preprints were considered, because of the need for use of rapidly accumulated information during the current situation. Reports on coronavirus-caused diseases other than COVID-19 were excluded.

We systematically searched PubMed, medRxiv, and CORD-19 (COVID-19 Open Research Dataset). The latter is probably the most extensive machine-readable literature collection specially created for the COVID-19 global crisis. We retrieved all relevant English literature from January 1, 2020, up to April 27, 2020 . We also searched references of initially retrieved articles. We used Boolean logic to create

To quantify the effect (if any) of the presence as opposed to absence of cancer on important clinical outcomes of patients with COVID-19. Knowledge Generated Cancer is associated with worse clinical outcomes among patients with COVID-19. However, elderly patients with cancer may not be at increased risk of death when infected with COVID-19.

The findings of the meta-analysis may inform discussions of clinicians with patients about prognosis and may guide health policies. the search key phrase ("clinical characteristics" OR comorbidities OR cancer OR malignancy) AND (COVID-19 OR 2019-nCoV OR SARS-CoV-2) AND (mortality OR morbidity OR severity OR ICU OR outcomes). When searching CORD-19, we replaced Boolean operators "AND" and "OR" with the symbols "+" and "|", respectively. When searching medRxiv, we used "COVID-19 cancer" as the main key phrase. Two authors (V.G.G. and E.P.) independently conducted the literature search and uploaded their findings in an online file storage service (Google Drive) to double-check them. They subsequently discussed the possibility of duplicate patient populations with the third author (I.I.S.). 4

Two authors (V.G.G. and E.P.) independently extracted data in a prespecified worksheet and cross-checked their findings. We collected data on type of publication, author, type of study, total patient population, outcomes of patients with versus without cancer, age, sex, and comorbidities. Authors of original contributions were contacted. Six authors provided us with additional information, which was incorporated in the findings of the meta-analysis.

We assessed the methodological quality of the retrieved observational cohort studies with the Tool to Assess Risk of Bias in Cohort Studies, developed by the CLARITY Group at McMaster University. 5 The tool uses 8 questions, with 4 possible answers in each. Clarifications on the risk-of-bias assessment are provided in the Data Supplement. Two authors (V.G.G. and E.P.) independently assessed the studies.

The results were discussed with the third author (I.I.S.).

The primary outcomes of the meta-analysis were all-cause mortality and need for ICU admission. The latter outcome included either actual admission to the ICU or severe disease (such as application of invasive mechanical ventilation) that required admission to the ICU, even if the original study did not specify whether such patients were indeed admitted in the ICU (more details are provided in the Data Supplement). We did so because patients with severe disease might occasionally be unable to be admitted to the ICU because of unavailability of enough beds.

We performed prespecified sensitivity analyses by calculating the pooled risk ratio (RR) of studies with low risk of bias and by excluding each study and recalculating the RR. We attempted prespecified subgroup analyses by age, type of cancer (solid tumor v hematologic malignancy), and country, but we were not able to perform the last 2 analyses because of unavailability of relevant data.

We conducted data synthesis using Review Manager 5.3 (RevMan 5.3) by the Cochrane Collaboration. 6 We expressed pooled dichotomous effect measures as RR with 95% CI. We used a random-effects (DerSimonian and Laird) model. We measured the presence of statistical heterogeneity with I 2 , interpreted according to the Cochrane Handbook recommendations 7 ; 0%-40%: might not be important; 30%-60%: may represent moderate heterogeneity; 50%-90%: substantial heterogeneity; 75%-100%: considerable heterogeneity. Cancer and COVID-19 Figure 1 shows the flow diagram for study selection. Regarding mortality data from China, we excluded presumably duplicate publications with overlapping enrollment dates to include only 1 overarching report from the Chinese Center for Disease Control and Prevention (CDC). 8 However, given that the latter report from the Chinese CDC did not provide specific data on old patients, 8 and 2 studies from China provided such data, 9, 10 we included these 2 studies in our subgroup analysis by age. A total of 32 studies (19 peer-reviewed, 13 preprints) involving 46,499 patients (1,776 patients with cancer) with COVID-19 from Asia, Europe, and the United States were included in our meta-analysis. Tables 1 and 2 list the summary characteristics and risk of bias assessment of the included studies, respectively.

Eight studies (37,807 total patients, 1,428 with cancer) provided data for all-cause mortality. 8, 12, 18, 22, 24, 26, 28, 29 No statistically significant heterogeneity was detected (I 2 = 37%). All-cause mortality was higher in patients with versus without cancer (2,034 deaths; RR, 1.66; 95% CI, 1.33 to 2.07; P , .0001; Fig 2) .

Twenty-six studies (15,375 total patients, 801 with cancer) provided data for need for ICU admission. [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [23] [24] [25] 27, 28, [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] Moderate significant heterogeneity was detected (I 2 = 53%). Patients with cancer were more likely to need ICU admission than patients without cancer (3,220 events; RR, 1.56; 95% CI, 1.31 to 1.87; P , .0001; Fig 3) .

In the sensitivity analysis of 4 studies with low risk of bias (8,804 total patients, 694 with cancer), all-cause mortality was higher in patients with versus without cancer (856 deaths; RR, 1.47; 95% CI, 1.04 to 2.09; P = .03). 12, 22, 24, 29 This was also the case for the sensitivity analyses by excluding each study and recalculating the RR.

In the prespecified subgroup analysis of 8 studies (5,438 patients, 505 with cancer), which provided data on mortality of patients . 65 years old, all-cause mortality was comparable between those with versus without cancer (915 deaths; RR, 1.06; 95% CI, 0.79 to 1.41; P = .71; Fig 4) . 9, 10, 12, 18, 22, 24, 26, 29 DISCUSSION By performing the most comprehensive meta-analysis to date, which incorporated data from . 46,000 patients with COVID-19 across almost all continents, we quantified the effect of cancer on all-cause mortality (RR, 1.66; 95% CI, 1.33 to 2.07) and need for ICU admission (RR, 1.56; 95% CI, 1.31 to 1.87). Also, by performing a prespecified subgroup analysis, we revealed the interesting finding that among patients . 65 years of age, all-cause mortality was comparable between those with versus without cancer.

It is important to quantify the effect of cancer on outcomes of patients with COVID-19, as there are conflicting reports in the literature. Several studies indicated that patients with cancer are more likely to develop severe disease and are at increased risk for poor prognosis. [40] [41] [42] They therefore encouraged clinicians to treat patients with cancer as an extremely vulnerable population. Those studies might also raise issues as to whether it is futile to admit patients with cancer and COVID-19 to the ICU. 43 On the other hand, other studies suggested that there was no evidence of elevated mortality rates among infected patients with cancer. 24, 44 An interesting theory even suggested that immunocompromised patients, such as patients with cancer, may dampen the so-called "cytokine storm" because of downregulated immune response and thus have comparable or even better clinical outcomes. 22, 45 The results of our meta-analysis might help to reveal the true effect of cancer on mortality and need for ICU admission. An interesting finding of the meta-analysis was that, when data were collected from older patients, the increased mortality risk in the presence of cancer did not seem obvious. Regardless of cancer presence, increased age is considered a factor of worse prognosis. 46, 47 Furthermore, older individuals are characterized by an increased prevalence of comorbidities, 48 which variably contribute to overall worse outcomes. 19 On considering the aforementioned, the observed absence of increased mortality risk in older individuals does not conflict with the main findings of the study; it rather implies that the presence of cancer may not further affect the already burdened prognosis among individuals age . 65 years.

Our meta-analysis has limitations. First, there are concerns for duplicate publications, 4 which might skew the results of any meta-analysis. In an attempt to minimize this risk, we excluded studies on mortality conducted in the same region with overlapping enrollment dates and we included only the results of the largest cohort. Second, data were not available to perform meaningful subgroup analyses by type of cancer (including treatment and immunosuppressive status). However, through communications with authors of original studies, we were able to carry out an important subgroup analysis by age.

In conclusion, by accumulating data from 32 studies involving 46,499 patients (1,776 patients with cancer) with COVID-19 from Asia, Europe, and the United States, we quantified the effect of cancer on important clinical outcomes, such as mortality and need for ICU admission. We also found that elderly patients with cancer may not be at increased risk of death when infected with COVID-19. The findings of the meta-analysis are important to clinicians, because they can inform discussions with patients about prognosis. They may also guide health policies regarding protection of this vulnerable population. 

Conception and design: All authors Collection and assembly of data: Vassilis G. Giannakoulis, Eleni Papoutsi Data analysis and interpretation: All authors Manuscript writing: All authors Final approval of manuscript: All authors Accountable for all aspects of the work: All authors

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs. org/go/site/misc/authors.html. Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).

No potential conflicts of interest were reported.

Latest global cancer data: Cancer burden rises to 18.1 million new cases and 9.6 million cancer deaths

Are cancer patients more vulnerable to COVID-19?

The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration

Editorial concern-possible reporting of the same patients with COVID-19 in different reports

Tool to Assess Risk of Bias in Cohort Studies. Contributed by the CLARITY Group at McMaster University

Version 5.3. Copenhagen, The Nordic Cochrane Centre, The Cochrane Collaboration

Cochrane Handbook for Systematic Reviews of Interventions version 6

The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team: The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) -China

Clinical characteristics and outcomes of older patients with coronavirus disease 2019 (COVID-19) in Wuhan

Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up

Characterization and clinical course of 1000 patients with COVID-19 in New York: Retrospective case series

SARS-COV-2 comorbidity network and outcome in hospitalized patients in

COVID-19 in a designated infectious diseases hospital outside Hubei Province

Clinical features of patients infected with the 2019 novel coronavirus (COVID-19

Epidemiological and clinical features of 291 cases with coronavirus disease 2019 in areas adjacent to Hubei, China: A doublecenter observational study

Clinical characteristics of coronavirus disease (COVID-19) early findings from a teaching hospital in Pavia

COVID-19 with different severity: A multi-center study of clinical features

Clinical characteristics of Covid-19 in

Comorbidity and its impact on 1590 patients with COVID-19 in China: A nationwide analysis

Clinical features of patients infected with 2019 novel coronavirus in Wuhan

Clinical features and management of severe COVID-19: A retrospective study in Wuxi

Outcomes of the 2019 novel coronavirus in patients with or without a history of cancer -a multi-centre North London experience

Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan

Do patients with cancer have a poorer prognosis of COVID-19? An experience in

Characteristics of Hospitalized Adults With COVID-19 in an Integrated Health Care System in California

Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in Iran: A single center study

Factors associated with hospitalization and critical illness among 4,103 patients with COVID-19 disease in New York City

Covid-19 testing, hospital admission, and intensive care among 2,026,227 United States Veterans aged 54-75 years

Characteristics and outcomes of a cohort of SARS-CoV-2 patients in the Province of Reggio Emilia

Clinical characteristics of imported and second-generation COVID-19 cases outside Wuhan, China: A multicenter retrospective study

Clinical features and treatment of COVID-19 patients in northeast Chongqing

Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China

Clinical features of 69 cases with coronavirus disease

Clinical characteristics of coronavirus disease 2019 in Hainan

Retrospective study of risk factors for severe SARS-Cov-2 infections in hospitalized adult patients

Clinical features and outcomes of 221 patients with COVID-19 in Wuhan

Risk factors for disease severity, unimprovement, and mortality in COVID-19 patients in Wuhan, China

CT features of SARS-CoV-2 pneumonia according to clinical presentation: a retrospective analysis of 120 consecutive patients from Wuhan city

Clinical characteristics and durations of hospitalized patients with COVID-19 in Beijing: A retrospective cohort study

A multicentre study of 2019 novel coronavirus disease outcomes of cancer patients in Wuhan

Clinical characteristics of COVID-19-infected cancer patients: A retrospective case study in three hospitals within Wuhan, China

Clinical characteristics and prognosis in cancer patients with COVID-19: A single center's retrospective study

Admission of critically ill patients with cancer to the ICU: Many uncertainties remain

Clinical factors predict deterioration among patients with cancer, COVID-19

Benign COVID-19 in an immunocompromised cancer patient -the case of a married couple

Severe outcomes among patients with coronavirus disease 2019 (COVID-19) -United States

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study

We thank Christopher T. Rentsch