Trends in Incidence Rates, Mortality Rates, and Age-Period-Cohort Effects of Female Breast Cancer — China, 2003–2017
Open accessAbstract
Introduction This study reported the trends in female breast cancer incidence and mortality rates in China, and analyzed the corresponding age-period-cohort effects. Methods Data from 22 population-based cancer registries in China between 2003 and 2017 were analyzed. Age-standardized incidence rates (ASIR) and mortality rates (ASMR) were calculated using Segi’s world standard population. Joinpoint regression was employed to evaluate trends, and age-period-cohort effects were examined using the intrinsic estimator method. Results The ASIR for female breast cancer exhibited a more rapid increase in rural areas compared to urban areas across all age groups. The most substantial increase was observed in the 20–34 age group in rural areas [annual percent change (APC)=9.0%, 95% confidence interval (CI): 7.0%–11.0%, P<0.001]. The ASMR for females under 50 years old remained stable from 2003 to 2017 in both urban and rural areas. However, the ASMR for females over 50 in rural areas and those over 65 in urban areas demonstrated a significant increase, with the most pronounced increase observed among females over 65 in rural areas (APC=4.9%, 95% CI: 2.8%–7.0%, P<0.001). Age-period-cohort analysis revealed increasing period effects and decreasing cohort effects for female breast cancer incidence and mortality rates in both urban and rural settings. Notably, the cohort effect for incidence displayed a slight upward trend for females born between 1983 and 1992 in rural areas. Conclusions Our study revealed a rapid increase in breast cancer incidence among younger generations and an accelerated mortality rate in older populations residing in rural areas. To effectively address the growing burden of female breast cancer in China, it is essential to develop and implement targeted intervention strategies.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Substantial geographic and temporal variations in breast cancer mortality in different regions appear to be linked to the level of coverage of essential health services.
“There remain substantial geographic and temporal variations in breast cancer mortality in different regions 54,56 that appear to be linked to the level of coverage of essential health services.57”
From Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. (2024) · cites this paper as [54]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Cancer incidence and mortality in China, 2016
Zheng, R., Sun, K., Han, B., Li, L., Chen, R., Wang, S., Li, L., Zeng, H., He, J., Wei, W., et al. (2022) · Journal of the National Cancer Center · doi:10.1016/j.jncc.2022.02.002 · Cited by 1,516 · see citing works
Self-citationGlobal burden and trends in premenopausal and postmenopausal breast cancer: a population-based study
Heer, E., Harper, A., Escandor, N., Sung, H., McCormack, V., & Fidler-Benaoudia, M. M. (2020) · The Lancet Global Health · doi:10.1016/s2214-109x(20)30215-1 · Cited by 888 · see citing works
Li, N., Deng, Y., Zhou, L., Tian, T., Yang, S., Wu, Y., Zheng, Y., Zhai, Z., Hao, Q., Song, D., et al. (2019) · Journal of Hematology & Oncology · doi:10.1186/s13045-019-0828-0 · Cited by 464 · see citing works
Global breast cancer incidence and mortality trends by region, age-groups, and fertility patterns
Lima, S. M., Kehm, R. D., & Terry, M. B. (2021) · EClinicalMedicine · doi:10.1016/j.eclinm.2021.100985 · Cited by 299 · see citing works
Chen, W., Xia, C., Zheng, R., Zhou, M., Lin, C., Zeng, H., Zhang, S., Wang, L., Yang, Z., Sun, K., et al. (2019) · The Lancet Global Health · doi:10.1016/s2214-109x(18)30488-1 · Cited by 290 · see citing works
Self-citationBreast cancer incidence and mortality in women in China: temporal trends and projections to 2030
Lei, S., Zheng, R., Zhang, S., Chen, R., Wang, S., Sun, K., Zeng, H., Wei, W., & He, J. (2021) · Cancer Biology and Medicine · doi:10.20892/j.issn.2095-3941.2020.0523 · Cited by 269 · see citing works
Self-citationLambertini, M., Santoro, L., Mastro, L. D., Nguyen, B., Livraghi, L., Ugolini, D., Peccatori, F. A., & Azim, H. A. (2016) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2016.07.006 · Cited by 249 · see citing works
Zeng, H., Ran, X., An, L., et al. (2021) · The Lancet Public Health · doi:10.1016/s2468-2667(21)00157-2 · Cited by 219 · see citing works
Self-citationMubarik, S., Malik, S. S., Wang, Z., et al. (2019) · Cancer Management and Research · doi:10.2147/cmar.s208323 · Cited by 62 · see citing works
Yadav, S., LaDuca, H., Polley, E. C., et al. (2020) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djaa167 · Cited by 37 · see citing works
Wang, J., Lv, H., Xue, Z., et al. (2018) · BioMed Research International · doi:10.1155/2018/5307459 · Cited by 36 · see citing works
Ding, Y., Chen, X., Zhang, Q., et al. (2020) · BMC Public Health · doi:10.1186/s12889-020-09375-0 · Cited by 24 · see citing works
Risk Factors for Female Breast Cancer: A Population Cohort Study
Wang, Y.-C., Lin, C., Huang, S., Chen, M., & Lee, T. (2022) · Cancers · doi:10.3390/cancers14030788 · Cited by 20 · see citing works
Krishnamoorthy, Y., Rajaa, S., Giriyappa, D. K., et al. (2020) · Journal of Research in Medical Sciences · doi:10.4103/jrms.jrms_708_19 · Cited by 12 · see citing works
Luan, H., Luo, L.-S., & Lu, Z. (2021) · International Journal of Public Health · doi:10.3389/ijph.2021.603810 · Cited by 8 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., & Jemal, A. (2024) · CA: a cancer journal for clinicians · doi:10.3322/caac.21834 · Cited by 27,064 · see citing works
- Authors
- Sun, K., National Central Cancer Registry, N. C. C. C. R. C. F. C. H., Lei, L., Zheng, R., Zhang, S., Zeng, H., Wang, S., Li, L., Chen, R., Han, B., Peng, J., Wei, W., He, J., Shenzhen Center for Chronic Disease Control, S. C., & Department of Thoracic Surgery, N. C. C. C. R. C. F. C. H.
- Affiliations
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Corresponding author
- Wei, Wenqiang
- He, Jie
- ORCID
- Venue
- China CDC Weekly
- Published
- 2023
- Volume
- 5
- Issue
- 15
- Pages
- 340-346
- ISSN
- 2096-7071 (ISSN-L)
- PMC
- PMC10182910
- OpenAlex
- W4365803554
- Cited by
- 27
- References
- 15
- Citations by year
- 2026: 6 · 2025: 15 · 2024: 5 · 2023: 1
- FWCI
- 3.29
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- China CDC Weekly (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Funders
- Government of Jiangsu Province
- Sanming Project of Medicine in Shenzhen
- Topics
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Health Sciences › Medicine › Oncology › Cancer Risks and Factors
- Health Sciences › Medicine › Pathology and Forensic Medicine › Breast Lesions and Carcinomas
- Keywords
- female breast cancer, cancer incidence trends, cancer mortality trends, age-period-cohort analysis, urban-rural differences, young women, older women, cohort effects, period effects, China
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