Cancer associates with risk and severe events of COVID-19: A systematic review and meta-analysis

Abstract

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 7094 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 < .001) overall and 3.2% (95% CL [0.023, 0.041]; P < .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 < .001) and death (OR = 2.97, 95% CL [1.48, 5.96]; P = .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.

Keywords: COVID-19; cancer; comorbidity; meta-analysis; severe events.

FIGURE 1

Flowchart of the literature search and selection process

FIGURE 2

Forest plot for meta‐analysis of cancer prevalence in patients with COVID‐19

FIGURE 3

Forest plot for meta‐analysis of cancer prevalence in patients with COVID‐19 from Hubei

FIGURE 4

Forest plots of the meta‐analysis of the association of cancer with severe events of COVID‐19 (A, severe cases; B, death)

FIGURE 5

Plots for publication bias assessment (x‐axis, precision or SE; y‐axis, effect size; dot, individual study; circle size represents the weight of individual study). A, Begg's plot with filled studies for meta‐analysis of cancer prevalence in all samples; B, Begg's plot with filled studies for Hubei only of cancer prevalence in Hubei; C, Begg's plot for meta‐analysis of association with severe events; D, Egger's publication plot for publication bias in studies of severe events