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Development and external validation of a breast cancer absolute risk prediction model in Chinese population

Overview of attention for article published in Breast Cancer Research, May 2021
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  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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3 X users

Citations

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Title
Development and external validation of a breast cancer absolute risk prediction model in Chinese population
Published in
Breast Cancer Research, May 2021
DOI 10.1186/s13058-021-01439-2
Pubmed ID
Authors

Yuting Han, Jun Lv, Canqing Yu, Yu Guo, Zheng Bian, Yizhen Hu, Ling Yang, Yiping Chen, Huaidong Du, Fangyuan Zhao, Wanqing Wen, Xiao-Ou Shu, Yongbing Xiang, Yu-Tang Gao, Wei Zheng, Hong Guo, Peng Liang, Junshi Chen, Zhengming Chen, Dezheng Huo, Liming Li

Abstract

In contrast to developed countries, breast cancer in China is characterized by a rapidly escalating incidence rate in the past two decades, lower survival rate, and vast geographic variation. However, there is no validated risk prediction model in China to aid early detection yet. A large nationwide prospective cohort, China Kadoorie Biobank (CKB), was used to evaluate relative and attributable risks of invasive breast cancer. A total of 300,824 women free of any prior cancer were recruited during 2004-2008 and followed up to Dec 31, 2016. Cox models were used to identify breast cancer risk factors and build a relative risk model. Absolute risks were calculated by incorporating national age- and residence-specific breast cancer incidence and non-breast cancer mortality rates. We used an independent large prospective cohort, Shanghai Women's Health Study (SWHS), with 73,203 women to externally validate the calibration and discriminating accuracy. During a median of 10.2 years of follow-up in the CKB, 2287 cases were observed. The final model included age, residence area, education, BMI, height, family history of overall cancer, parity, and age at menarche. The model was well-calibrated in both the CKB and the SWHS, yielding expected/observed (E/O) ratios of 1.01 (95% confidence interval (CI), 0.94-1.09) and 0.94 (95% CI, 0.89-0.99), respectively. After eliminating the effect of age and residence, the model maintained moderate but comparable discriminating accuracy compared with those of some previous externally validated models. The adjusted areas under the receiver operating curve (AUC) were 0.634 (95% CI, 0.608-0.661) and 0.585 (95% CI, 0.564-0.605) in the CKB and the SWHS, respectively. Based only on non-laboratory predictors, our model has a good calibration and moderate discriminating capacity. The model may serve as a useful tool to raise individuals' awareness and aid risk-stratified screening and prevention strategies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 15%
Student > Master 4 12%
Other 2 6%
Student > Postgraduate 2 6%
Professor > Associate Professor 2 6%
Other 3 9%
Unknown 15 45%
Readers by discipline Count As %
Medicine and Dentistry 8 24%
Nursing and Health Professions 4 12%
Unspecified 1 3%
Business, Management and Accounting 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 2 6%
Unknown 16 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 August 2021.
All research outputs
#15,751,285
of 25,392,582 outputs
Outputs from Breast Cancer Research
#1,388
of 2,054 outputs
Outputs of similar age
#239,085
of 460,098 outputs
Outputs of similar age from Breast Cancer Research
#11
of 24 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,054 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 460,098 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.