Abstract
BackgroundThis study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers.MethodsThis case–control study of 1204 women aged 47–73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG). A radiologist assessed BD using a visual analogue scale (VAS) from 0 to 100. Logistic regression and area under the receiver operating characteristic curves (AUC) determined whether BD could predict mode of detection (screen-detected or interval); node-negative cancers; node-positive cancers, and all cancers vs. controls.ResultsFGV, VBD, VAS, and DG all discriminated interval cancers (all p < 0.01) from controls. Only FGV-quartile discriminated screen-detected cancers (p < 0.01). Based on AUC, FGV discriminated all cancer types better than VBD or VAS. FGV showed a significantly greater discrimination of interval cancers, AUC = 0.65, than of screen-detected cancers, AUC = 0.61 (p < 0.01) as did VBD (0.63 and 0.53, respectively, p < 0.001).ConclusionFGV, VBD, VAS and DG discriminate interval cancers from controls, reflecting some masking risk. Only FGV discriminates screen-detected cancers perhaps adding a unique component of breast cancer risk.
Highlights
This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers
For the 297 interval cancers, the time between screening and diagnosis was an average of 656 days
A higher proportion of screendetected than interval cancers were in situ, and a higher proportion of interval cancers were node-positive
Summary
This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers. CONCLUSION: FGV, VBD, VAS and DG discriminate interval cancers from controls, reflecting some masking risk. The aim of stratified, or risk-based, breast cancer screening [1,2,3,4,5] is to optimise the balance of benefits of early cancer detection and mortality reduction with the harms of false-positive mammograms, benign biopsies, and overdiagnosis [4]. Stratified protocols would personalise mammography initiation, screening interval, and supplemental screening with other modalities in order to decrease advanced and interval cancers, while maintaining low rates of false positives. This programme would ideally decrease mortality from breast cancer in all women regardless of risk. Automated quantitative BD [17,18,19,20,21] would enable more consistent density assessment, and potentially risk assessment for use in breast cancer
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