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Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status

Overview of attention for article published in Breast Cancer Research, December 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

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4 tweeters

Citations

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22 Dimensions

Readers on

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38 Mendeley
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Title
Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status
Published in
Breast Cancer Research, December 2016
DOI 10.1186/s13058-016-0778-1
Pubmed ID
Authors

Serghei Malkov, John A. Shepherd, Christopher G. Scott, Rulla M. Tamimi, Lin Ma, Kimberly A. Bertrand, Fergus Couch, Matthew R. Jensen, Amir P. Mahmoudzadeh, Bo Fan, Aaron Norman, Kathleen R. Brandt, V. Shane Pankratz, Celine M. Vachon, Karla Kerlikowske

Abstract

Several studies have shown that mammographic texture features are associated with breast cancer risk independent of the contribution of breast density. Thus, texture features may provide novel information for risk stratification. We examined the association of a set of established texture features with breast cancer risk by tumor type and estrogen receptor (ER) status, accounting for breast density. This study combines five case-control studies including 1171 breast cancer cases and 1659 controls matched for age, date of mammogram, and study. Mammographic breast density and 46 breast texture features, including first- and second-order features, Fourier transform, and fractal dimension analysis, were evaluated from digitized film-screen mammograms. Logistic regression models evaluated each normalized feature with breast cancer after adjustment for age, body mass index, first-degree family history, percent density, and study. Of the mammographic features analyzed, fractal dimension and second-order statistics features were significantly associated (p < 0.05) with breast cancer. Fractal dimensions for the thresholds equal to 10% and 15% (FD_TH10 and FD_TH15) were associated with an increased risk of breast cancer while thresholds from 60% to 85% (FD_TH60 to FD_TH85) were associated with a decreased risk. Increasing the FD_TH75 and Energy feature values were associated with a decreased risk of breast cancer while increasing Entropy was associated with a decreased risk of breast cancer. For example, 1 standard deviation increase of FD_TH75 was associated with a 13% reduced risk of breast cancer (odds ratio = 0.87, 95% confidence interval 0.79-0.95). Overall, the direction of associations between features and ductal carcinoma in situ (DCIS) and invasive cancer, and estrogen receptor positive and negative cancer were similar. Mammographic features derived from film-screen mammograms are associated with breast cancer risk independent of percent mammographic density. Some texture features also demonstrated associations for specific tumor types. For future work, we plan to assess risk prediction combining mammographic density and features assessed on digital images.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 29%
Student > Master 6 16%
Student > Ph. D. Student 5 13%
Professor > Associate Professor 4 11%
Student > Doctoral Student 2 5%
Other 7 18%
Unknown 3 8%
Readers by discipline Count As %
Medicine and Dentistry 16 42%
Biochemistry, Genetics and Molecular Biology 3 8%
Nursing and Health Professions 3 8%
Engineering 3 8%
Computer Science 3 8%
Other 6 16%
Unknown 4 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 11 December 2016.
All research outputs
#2,122,339
of 8,755,198 outputs
Outputs from Breast Cancer Research
#316
of 1,070 outputs
Outputs of similar age
#93,879
of 299,761 outputs
Outputs of similar age from Breast Cancer Research
#9
of 25 outputs
Altmetric has tracked 8,755,198 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,070 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 299,761 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 25 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 64% of its contemporaries.