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Eur J Radiol. 2019 Jan;110:81-87. doi: 10.1016/j.ejrad.2018.11.012. Epub 2018 Nov 15.

Mammographic breast density: How it affects performance indicators in screening programmes?

Author information

1
Department of Epidemiology and Evaluation, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Research Network on Health Services in Chronic Diseases (REDISSEC), Barcelona, Spain.
2
Department of Epidemiology and Evaluation, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Research Network on Health Services in Chronic Diseases (REDISSEC), Barcelona, Spain; European Higher Education Area (EHEA), Doctoral Programme in Methodology of Biomedical Research and Public Health in Department of Pediatrics, Obstetrics and Gynecology, Preventive Medicine and Public Health, Universitat Autónoma de Barcelona (UAB), Bellaterra, Barcelona, Spain.
3
General Directorate of Public Health, Government of Cantabria, Santander, Spain.
4
Cancer Prevention and Monitoring Program, Catalan Institute of Oncology, Barcelona, Spain.
5
Research Network on Health Services in Chronic Diseases (REDISSEC), Barcelona, Spain; Clinical Epidemiology and Cancer Screening, Parc Taulí University Hospital, Sabadell, Spain.
6
Department of Epidemiology and Evaluation, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Research Network on Health Services in Chronic Diseases (REDISSEC), Barcelona, Spain. Electronic address: xcastells@parcdesalutmar.cat.

Abstract

OBJECTIVES:

To investigate how breast density affects screening performance indicators in a digital mammography context.

METHODS:

We assessed the effect of breast density over the screen-detected and interval cancers rates, false-positives, specificity, sensitivity, recall rate, positive predictive value of recall (PPV-1), and PPV of invasive tests (PPV-2). Radiologists classified breast density using the BIRADS System. We used generalized estimating equations to account for within-woman correlation by means of the robust Huber-White variance estimator.

RESULTS:

We included 177,164 women aged 50-69 years who underwent 499,251 digital mammograms from 2004 to 2015 in Spain. According to the fibroglandular tissue percentage, 24.7% of mammograms were classified as BI-RADS 1 (<25% glandular), 54.7% as BI-RADS 2 (25-50% glandular), 14.0% as BI-RADS 3 (51-75% glandular) and 6.6% as BI-RADS 4 (>75% glandular). Overall, women with BI-RADS 3 had the highest screen-detected cancer rate (5.9 per 1000) and BI-RADS 4 the highest interval cancer rate (2.4 per 1000). Sensitivity decreased from 89.2% in women with BI-RADS 1 to 67.9% in BI-RADS 4. Both PPV-1 and PPV-2 decreased from 10.4% to 5.7% and from 49.8% to 32.4% in women with BI-RADS 1 and BI-RADS 4, respectively. Women aged 60-69 years with BI-RADS 4 had the lowest sensitivity (54.9%) and the highest interval cancer rate (3.8 per 1000).

CONCLUSIONS:

Performance screening measures are negatively affected by breast density falling to a lower sensitivity and PPV, and higher interval cancer rate as breast density increases. Particularly women aged 60-69 years with >75% glandular breasts had the worst results and therefore may be candidates for screening using other technologies.

KEYWORDS:

Breast density; Breast neoplasms; Early detection of cancer; Mammography

PMID:
30599878
DOI:
10.1016/j.ejrad.2018.11.012
[Indexed for MEDLINE]

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