Breast density effect on the sensitivity of digital screening mammography in a UK cohort

Author:

Payne Nicholas R.,Hickman Sarah E.,Black Richard,Priest Andrew N.,Hudson Sue,Gilbert Fiona J.ORCID

Abstract

Abstract Objectives To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort. Methods Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50–60 and 61–70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold. Results Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5. Conclusions The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations. Clinical relevance statement In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category. Key Points Breast density can mask cancers leading to underdiagnosis on mammography. Interval cancer rate increased with breast density categories ‘a’ to ‘d’; 1.8 to 7.9 per thousand. Recall rates increased with increasing breast density, leading to more false positive recalls.

Publisher

Springer Science and Business Media LLC

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