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Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study

Overview of attention for article published in Breast Cancer Research, June 2016
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Title
Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study
Published in
Breast Cancer Research, June 2016
DOI 10.1186/s13058-016-0722-4
Pubmed ID
Authors

Kavitha Krishnan, Laura Baglietto, Carmel Apicella, Jennifer Stone, Melissa C. Southey, Dallas R. English, Graham G. Giles, John L. Hopper

Abstract

Risk of screen-detected breast cancer mostly reflects inherent risk, while risk of interval cancer reflects inherent risk and risk of masking (risk of the tumor not being detected due to increased dense tissue). Therefore the predictors of whether a breast cancer is interval or screen-detected include those that predict masking. Our aim was to investigate the associations between mammographic measures and (1) inherent risk, and (2) masking. We conducted a case-control study nested within the Melbourne collaborative cohort study of 244 screen-detected cases (192 small tumors (<2 cm)) matched to 700 controls and 148 interval cases (76 small tumors) matched to 446 controls. Dense area (DA), percent dense area (PDA), and non-dense area (NDA) were measured using the Cumulus software. Conditional and unconditional logistic regression were applied as appropriate to estimate the odds per adjusted standard deviation (OPERA) adjusted for age and body mass index (BMI), allowing for the association with BMI to be a function of age at diagnosis. Tests of fit were performed using the Bayesian information criterion (BIC) and the area under the receiver operating characteristic curve. For screen-detected cancer, the association with BMI had a marginally significant dependence on age at diagnosis, and after adjustment both DA and PDA were associated with risk (OPERA approximately 1.2) and gave a similar fit. NDA was not associated with risk. For interval cancer, the BMI risk association was not dependent on age at diagnosis and the best fitting model was PDA alone (OPERA = 2.24, 95 % confidence interval 1.75, 2.86). Prediction of interval versus screen-detected cancer was best achieved by PDA alone (OPERA = 1.76, 95 % confidence interval 1.39, 2.22) with no association with BMI. When the analysis was restricted to small tumors to reduce the influence of tumor growth, we obtained similar results. Inherent breast cancer risk is predicted by BMI and DA or PDA, but not NDA. Masking is predicted by PDA, and not by BMI. Understanding risk and masking could help tailor mammographic screening.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 24%
Student > Ph. D. Student 4 19%
Student > Bachelor 3 14%
Student > Postgraduate 2 10%
Researcher 2 10%
Other 2 10%
Unknown 3 14%
Readers by discipline Count As %
Medicine and Dentistry 9 43%
Nursing and Health Professions 3 14%
Agricultural and Biological Sciences 2 10%
Computer Science 1 5%
Psychology 1 5%
Other 2 10%
Unknown 3 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 19 June 2016.
All research outputs
#6,854,462
of 7,917,108 outputs
Outputs from Breast Cancer Research
#892
of 1,004 outputs
Outputs of similar age
#219,772
of 262,522 outputs
Outputs of similar age from Breast Cancer Research
#32
of 33 outputs
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