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Published in: Breast Cancer Research 1/2018

Open Access 01-12-2018 | Research Article

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

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

Published in: Breast Cancer Research | Issue 1/2018

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Abstract

Background

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.

Methods

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.

Results

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).

Conclusions

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.
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Metadata
Title
A comparison of five methods of measuring mammographic density: a case-control study
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
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2018
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-018-0932-z

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