{Reference Type}: Journal Article
{Title}: Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case-control study.
{Author}: Burnside ES;Warren LM;Myles J;Wilkinson LS;Wallis MG;Patel M;Smith RA;Young KC;Massat NJ;Duffy SW;
{Journal}: Br J Cancer
{Volume}: 125
{Issue}: 6
{Year}: 09 2021
{Factor}: 9.075
{DOI}: 10.1038/s41416-021-01466-y
{Abstract}: 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.<BR>This 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.<BR>FGV, 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).<BR>FGV, 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.