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A comparison of five methods of measuring mammographic density: a case-control study

Overview of attention for article published in Breast Cancer Research, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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11 X users

Citations

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83 Dimensions

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128 Mendeley
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1 CiteULike
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Title
A comparison of five methods of measuring mammographic density: a case-control study
Published in
Breast Cancer Research, February 2018
DOI 10.1186/s13058-018-0932-z
Pubmed ID
Authors

Susan M. Astley, Elaine F. Harkness, Jamie C. Sergeant, Jane Warwick, Paula Stavrinos, Ruth Warren, Mary Wilson, Ursula Beetles, Soujanya Gadde, Yit Lim, Anil Jain, Sara Bundred, Nicola Barr, Valerie Reece, Adam R. Brentnall, Jack Cuzick, Tony Howell, D. Gareth Evans

Abstract

High mammographic density is associated with both risk of cancers being missed at mammography, and increased risk of developing breast cancer. Stratification of breast cancer prevention and screening requires mammographic density measures predictive of cancer. This study compares five mammographic density measures to determine the association with subsequent diagnosis of breast cancer and the presence of breast cancer at screening. Women participating in the "Predicting Risk Of Cancer At Screening" (PROCAS) study, a study of cancer risk, completed questionnaires to provide personal information to enable computation of the Tyrer-Cuzick risk score. Mammographic density was assessed by visual analogue scale (VAS), thresholding (Cumulus) and fully-automated methods (Densitas, Quantra, Volpara) in contralateral breasts of 366 women with unilateral breast cancer (cases) detected at screening on entry to the study (Cumulus 311/366) and in 338 women with cancer detected subsequently. Three controls per case were matched using age, body mass index category, hormone replacement therapy use and menopausal status. Odds ratios (OR) between the highest and lowest quintile, based on the density distribution in controls, for each density measure were estimated by conditional logistic regression, adjusting for classic risk factors. The strongest predictor of screen-detected cancer at study entry was VAS, OR 4.37 (95% CI 2.72-7.03) in the highest vs lowest quintile of percent density after adjustment for classical risk factors. Volpara, Densitas and Cumulus gave ORs for the highest vs lowest quintile of 2.42 (95% CI 1.56-3.78), 2.17 (95% CI 1.41-3.33) and 2.12 (95% CI 1.30-3.45), respectively. Quantra was not significantly associated with breast cancer (OR 1.02, 95% CI 0.67-1.54). Similar results were found for subsequent cancers, with ORs of 4.48 (95% CI 2.79-7.18), 2.87 (95% CI 1.77-4.64) and 2.34 (95% CI 1.50-3.68) in highest vs lowest quintiles of VAS, Volpara and Densitas, respectively. Quantra gave an OR in the highest vs lowest quintile of 1.32 (95% CI 0.85-2.05). Visual density assessment demonstrated a strong relationship with cancer, despite known inter-observer variability; however, it is impractical for population-based screening. Percentage density measured by Volpara and Densitas also had a strong association with breast cancer risk, amongst the automated measures evaluated, providing practical automated methods for risk stratification.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 128 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 15%
Student > Bachelor 15 12%
Student > Ph. D. Student 14 11%
Student > Master 12 9%
Student > Postgraduate 8 6%
Other 19 15%
Unknown 41 32%
Readers by discipline Count As %
Medicine and Dentistry 39 30%
Nursing and Health Professions 13 10%
Biochemistry, Genetics and Molecular Biology 8 6%
Engineering 6 5%
Physics and Astronomy 5 4%
Other 15 12%
Unknown 42 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 08 July 2021.
All research outputs
#4,590,757
of 25,382,440 outputs
Outputs from Breast Cancer Research
#530
of 2,054 outputs
Outputs of similar age
#93,771
of 445,948 outputs
Outputs of similar age from Breast Cancer Research
#6
of 20 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
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 has gotten more attention than average, scoring higher than 74% 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 445,948 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 20 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 70% of its contemporaries.