The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Cancer burden of major cancers in China: A need for sustainable actions
Open accessAbstract
Cancer is still a major health problem in China although numerous efforts have been made for its prevention and control. Findings from this study showed that lung cancer remains the most common type of cancer diagnosed, and was attributed to nearly 30% of all cancer‐related deaths. The incidence of the five most common cancers, in China, in 2015, including cancers of the lungs, stomach, colorectum, liver and breast, accounted for almost 60% of all cancers diagnosed. The high cancer burden in China highlights the need for further improvement in health education, professional training and the building up an anti‐cancer network for introducing and implementing sustainable actions for cancer control.
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Citations
Cites
Siegel, R. L., Miller, K. D., & Jemal, A. (2020) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21590 · Cited by 20,444
Cancer statistics in China, 2015
Chen, W., Zheng, R., Baade, P. D., Zhang, S., Zeng, H., Bray, F., Jemal, A., Yu, X. Q., & He, J. (2016) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21338 · Cited by 17,038
Self-citation
Cited by
Qiu, H., Cao, S., & Xu, R. (2021) · Cancer Communications · doi:10.1002/cac2.12197 · Cited by 1,015
Metadata
- Authors
- Cao, M., Li, H., Sun, D., & Chen, W.
- Venue
- Cancer Communications
- Published
- 2020-05
- Volume
- 40
- Issue
- 5
- Pages
- 205-210
- ISSN
- 1000-467X (ISSN-L)
- 2523-3548
- OpenAlex
- W3021119615
- Cited by
- 437
- References
- 2
- FWCI
- 22.30
- Type
- journal article
- Language
- en
- Open access
- gold
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- Cao, M., Li, H., Sun, D., & Chen, W. (2020). Cancer burden of major cancers in China: A need for sustainable actions. Cancer Communications. https://doi.org/10.1002/cac2.12025
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
