The DOI matches its Crossref record; 61 of the 64 references it cites were found in a registry or an index.
Cancer associates with risk and severe events of COVID ‐19: A systematic review and meta‐analysis
Open accessAbstract
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This is particularly true of older adults with cancer, who may be among the most vulnerable to the effects of COVID-19 due to their immunocompromised status and increased presence of comorbidities [1,2,3,4,5].”
From The Psychosocial Impact of COVID-19 on Older Adults with Cancer: A Rapid Review (2022) · cites this paper as [4]
In the citing paper
“Older adults diagnosed with both cancer and COVID-19 face increased mortality, hospitalization, and ICU admission [3,4,5].”
From The Psychosocial Impact of COVID-19 on Older Adults with Cancer: A Rapid Review (2022) · cites this paper as [4]
Citations
Cites
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Self-citationPreferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., Xiang, H., Cheng, Z., Xiong, Y., et al. (2020) · JAMA · doi:10.1001/jama.2020.1585 · Cited by 20,148
La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
Martínez González, M. (2020) · DSPACE System - Metalibrary (University of the Coast) · Cited by 18,463
Wu, Z., & McGoogan, J. M. (2020) · JAMA · doi:10.1001/jama.2020.2648 · Cited by 17,016
Flagged first, then by citations
3 of the 64 references couldn’t be matched to a known paper.
Research works printed but not linked: 6
- Fang XW, 2020, Clinical characteristics and treatment analysis of 79 patients infected with SARS‐CoV‐2, Chin Pharmacol Bull, 36, 453
- Li D, 2020, Clinical characteristics of 80 patients with COVID‐19 in Zhozhou city, Chin J Infect Control, 19, 227
- Li YL, 2020, Comparative study for clinical features between COVID‐19 patients with conventional type and heavy/critical type, Pract J Cardiac Cereb Pneumal Vasc Dis, 28, 14
- Sun DF, 2020, Clinical analysis of 30 patients infected with SARS‐CoV‐2, Zhejiang Clin Med, 22, 354
- Wang F, 2020, Clinical characteristics of 29 patients with COVID‐19 in Ningxia city, Ningxia Med J, 42, 263
- Tuo JY, 2016, Cancer incidence and mortality in cancer registries in Hubei Province, 2012, Cancer Res Prev Treat, 43, 974
Cited by
Sorted by citations
Items 101–128 of 128
Youssfi, I., Mechergui, N., Ziedi, H., Mersni, M., Chemingui, S., Haouari, W., Aouida, D., Youssef, I., & Ladhari, N. (2024) · Work · doi:10.3233/wor-230352 · Cited by 1
Razavi, S. E., Khodadadi, H., & Goharimanesh, M. (2024) · IET Systems Biology · doi:10.1049/syb2.12093 · Cited by 1
Randrian, V., Dhimene, A., Pillet, A., Evrard, C., Elfadel, R., Boyer, C., de Salins, A. G. D., Ingrand, I., Ferru, A., Rouleau, L., et al. (2025) · BMC Cancer · doi:10.1186/s12885-025-13787-9 · Cited by 1
Greathouse, F. R., Nagia, S. T., Rayyan, M., & Bailey, B. A. (2021) · Journal of Primary Care & Community Health · doi:10.1177/21501327211014722 · Cited by 1
Rahimi, H., Allahyari, A., Azimi, S. A., Kamandi, M., Mozaheb, Z., Zemorshidi, F., Khadem‐Rezaiyan, M., Bary, A., Seddigh‐Shamsi, M., & Nodeh, M. M. (2021) · Trials · doi:10.1186/s13063-021-05292-8 · Cited by 1
Arayıcı, M. E., Başbınar, Y., & Ellıdokuz, H. (2022) · Research Square · doi:10.21203/rs.3.rs-1922956/v1 · Cited by 1
COVID-19 and cancer: an extensive review
Mello, T. D. S., Azevedo, R. B., de-Hollanda, J. V. G., Ferreira, L. V. L., & Montalvão, F. (2021) · Brazilian Journal of Oncology · doi:10.5935/2526-8732.20210022
22066 接合具の降伏を一部許容した集成材一層門型ラーメンの耐力・変形能力
小松, 幸., 軽部, 正., 福田, 一., & 原, 康. (1995) · 学術講演梗概集. C-1, 構造III, 木質構造, 鉄骨構造, 鉄骨鉄筋コンクリート構造
Possibility of Tumor Development in Cancer Patient with COVID-19
Mardani, M. (2022) · Archives of Clinical Infectious Diseases · doi:10.5812/archcid.122510
Impact of COVID-19 on Affected Individuals in Iraq Focusing on Deceased Cancer Patients
Alwan, N. A. S., Lami, F., Khaleel, H. A., & Alhilfi, R. A. (2022) · JCO Global Oncology · doi:10.1200/go.22.00001
Child with COVID-19: Nutrition in the Intensive Care Unit
Ненартович, И. А., Голобородько, Н. В., & Почкайло, А. С. (2022) · Клиническая инфектология и паразитология · doi:10.34883/pi.2022.11.1.024
Presentation and Severity of COVID-19 Among Cancer Patients
Matta, S., Bajpai, R. C., Shekhawat, R., & Singh, R. K. (2022) · Journal of Medical Evidence · doi:10.4103/jme.jme_63_21
Coronavirus Disease 2019-Associated Acute Kidney Injury Garners More Attention
Yan, M., Niu, W., & Li, P. (2021) · Integrative Medicine in Nephrology and Andrology · doi:10.4103/imna.imna_15_21
Self-citationHow, G. Y., & Pua, U. (2022) · Journal of interventional medicine · doi:10.1016/j.jimed.2022.09.004
Cellular Landscaping of COVID-19 and Gynaecological Cancers: An Infrequent Correlation
Bhattacharjee, R., Das, D., Bhadhuri, R., Chakraborty, S., Dey, T., Buragohain, R., Nath, A., Muduli, K., Barman, P., & Gundamaraju, R. (2022) · Journal of Oncology · doi:10.1155/2022/5231022
Szewczyk-Dąbrowska, A., Banasik, M., Dąbrowska, K., Kujawa, K., Bombała, W., Sebastian, A., Matera-Witkiewicz, A., Krupińska, M., Grata-Borkowska, U. T., Sokołowski, J., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12030878
Cusi, M. G., Giacomo, A. M. D., Anichini, G., Savellini, G. G., Terrosi, C., Gandolfo, C., & Maio, M. (2023) · Viruses · doi:10.3390/v15030614
Portugal, I. (2023) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.5.2023.tde-05052023-164617
Villaseñor-Echavarri, R., la Rosa-Martínez, D. D., Frías-Jiménez, E., Martin‐Onraët, A., Cruz‐Cruz, A., Herrera, L. A., & Vilar‐Compte, D. (2023) · Gaceta Médica de México · doi:10.24875/gmm.m23000780
Cáncer en tiempos de COVID-19. Enfoque práctico desde el proceso diagnóstico del triage respiratorio
Ortiz-González, J., Espinoza-Morales, E., & Coronel-Brizio, P. G. (2023) · Revista Médica de la Universidad Veracruzana · doi:10.25009/rmuv.2022.1.77
Villaseñor-Echavarri, R., la Rosa-Martínez, D. D., Frías-Jiménez, E., Martin‐Onraët, A., Cruz‐Cruz, A., Herrera, L. A., & Vilar‐Compte, D. (2023) · Gaceta Médica de México · doi:10.24875/gmm.23000038
Chávez, A. C. F., León, G. Y. O., León, E. E. Á., Moreno-Nuñez, P., Tomás, J. P., & Andrés, J. M. A. (2025) · Enfermedades Infecciosas y Microbiología Clínica · doi:10.1016/j.eimc.2024.12.007
Health risk assessment for severe COVID-19 in Taiwan: a multi-centre electronic health record study
Chang, Y.-H., Burton, W., Nguyen, P.-A., Khang, D. D., Chen, C.-I., Huang, C., Lam, C., Lin, W.-K., Wang, F., Phuc, P. T., et al. (2025) · Journal of Global Health · doi:10.7189/jogh.15.04236
van Marcke, C., Honoré, N., van der Elst, A., Beyaert, S., Derouane, F., Dumont, C., Aboubakar Nana, F., Baurain, J. F., Borbath, I., Collard, P., et al. (2021) · Figshare · doi:10.6084/m9.figshare.14634033
Genomics and Transcriptomics-Based Predictive and Prognostic Biomarkers
Bhatt, S., Kandelwal, A., Maiti, S., & Kalra, N. (2025) · Springer eBooks · doi:10.1007/978-981-96-9346-7_10
Chávez, A. C. F., Ordoñez-León, G. Y., Mendoza-Gómez, M. Y., Sánchez-Carmona, D. L., & Andrés, J. M. A. (2026) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2026.2615506
Mobile apps for cancer patient education: a technology foresight analysis
Ornellas, B. D. C., da Mata, L. R. F., Silva, B. M., Ferreira, E. B., Mazoni, S. R., & Vasques, C. I. (2026) · Supportive Care in Cancer · doi:10.1007/s00520-026-11112-z
Metadata
- Authors
- Tian, Y., Qiu, X., Wang, C., Zhao, J., Jiang, X., Niu, W., Huang, J., & Zhang, F.
- Affiliations
- Beijing University of Chinese Medicine (CN)
- China-Japan Friendship Hospital (CN)
- Peking University (CN)
- Corresponding author
- Niu, Wenquan
- Huang, Jinchang
- Zhang, Fengyu
- Venue
- International Journal of Cancer
- Publisher
- Wiley
- Published
- 2020-08-15
- Volume
- 148
- Issue
- 2
- Pages
- 363-374
- ISSN
- 0020-7136 (ISSN-L)
- 1097-0215
- PMC
- PMC7404763
- OpenAlex
- W3042427819
- Cited by
- 129
- References
- 64
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 6 · 2023: 22 · 2022: 42 · 2021: 41 · 2020: 7
- FWCI
- 3.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Cancer (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (81573736)
- Topics
- Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- COVID-19 pandemic, cancer comorbidity, disease severity, mortality, risk factors, Hubei Province, publication bias
- MeSH terms
- COVID-19, SARS-CoV-2, Humans, Neoplasms, Risk Factors, Severity of Illness Index, Comorbidity, Prevalence, Risk Assessment, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
