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Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds

Overview of attention for article published in Breast Cancer Research, June 2018
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Title
Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds
Published in
Breast Cancer Research, June 2018
DOI 10.1186/s13058-018-0979-x
Pubmed ID
Authors

Chao Wang, Adam R. Brentnall, Jack Cuzick, Elaine F. Harkness, D. Gareth Evans, Susan Astley

Abstract

The percentage of mammographic dense tissue (PD) defined by pixel value threshold is a well-established risk factor for breast cancer. Recently there has been some evidence to suggest that an increased threshold based on visual assessment could improve risk prediction. It is unknown, however, whether this also applies to volumetric density using digital raw mammograms. Two case-control studies nested within a screening cohort (ages of participants 46-73 years) from Manchester UK were used. In the first study (317 cases and 947 controls) cases were detected at the first screen; whereas in the second study (318 cases and 935 controls), cases were diagnosed after the initial mammogram. Volpara software was used to estimate dense tissue height at each pixel point, and from these, volumetric and area-based PD were computed at a range of thresholds. Volumetric and area-based PDs were evaluated using conditional logistic regression, and their predictive ability was assessed using the Akaike information criterion (AIC) and matched concordance index (mC). The best performing volumetric PD was based on a threshold of 5 mm of dense tissue height (which we refer to as VPD5), and the best areal PD was at a threshold level of 6 mm (which we refer to as APD6), using pooled data and in both studies separately. VPD5 showed a modest improvement in prediction performance compared to the original volumetric PD by Volpara with ΔAIC = 5.90 for the pooled data. APD6, on the other hand, shows much stronger evidence for better prediction performance, with ΔAIC = 14.52 for the pooled data, and mC increased slightly from 0.567 to 0.577. These results suggest that imposing a 5 mm threshold on dense tissue height for volumetric PD could result in better prediction of cancer risk. There is stronger evidence that area-based density with a 6 mm threshold gives better prediction than the original volumetric density metric.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 22%
Student > Master 3 8%
Researcher 3 8%
Other 2 5%
Librarian 2 5%
Other 5 14%
Unknown 14 38%
Readers by discipline Count As %
Medicine and Dentistry 9 24%
Nursing and Health Professions 5 14%
Computer Science 2 5%
Engineering 2 5%
Psychology 1 3%
Other 3 8%
Unknown 15 41%
Attention Score in Context

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 09 June 2018.
All research outputs
#17,292,294
of 25,382,440 outputs
Outputs from Breast Cancer Research
#1,536
of 2,054 outputs
Outputs of similar age
#221,045
of 342,171 outputs
Outputs of similar age from Breast Cancer Research
#25
of 35 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% 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 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.