Evidence map›Paper›PMID 32683687›Full record

SynthesisInternational journal of cancer2021

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

Yehong Tian, Xiaowei Qiu, Chengxiang Wang, Jianxin Zhao, Xin Jiang, Wenquan Niu, Jinchang Huang, Fengyu Zhang

Abstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in International journal of cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 14 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed, 14 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

89 citing papers in PubMed, 14 syntheses or guidelines pooled it.

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  5. Immunological and clinical efficacy of COVID-19 vaccines in immunocompromised populations: a systematic review.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022
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  15. Trial
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  18. Mobile apps for cancer patient education: a technology foresight analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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29 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yehong TianThe Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.
Xiaowei QiuThe Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.
Chengxiang WangThe Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.
Jianxin ZhaoThe Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.
Xin JiangThe Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.
Wenquan NiuInstitute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Jinchang HuangThe Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.ORCID 0000-0002-9331-664X
Fengyu ZhangBeijing Huilongguan Hospital & Peking University Huilongguan Clinical Medical School, Beijing, China.

Funding

Beijing Haiju Scholarship BHTO201511097Key Research Project of Beijing University of Chinese Medicine 2020-JYB-ZDGG-143-1National Natural Science Foundation of China 81573736
6 · The paper itself

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.

Indexed as

ComorbidityCOVID-19HumansNeoplasmsPandemicsPrevalenceRisk AssessmentRisk FactorsSARS-CoV-2Severity of Illness IndexcancercomorbidityCOVID-19meta-analysissevere events

Identifiers

PMID32683687
PMCPMC7404763

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.