Breast Density and Risk of Interval Cancers

Objectives Breast cancer prognosis is better for smaller tumours. Women with high breast density are at higher risk of breast cancer and have larger screen-detected and interval cancers in mammographic screening programmes. We assess which continuous measures of breast density are the strongest predictors of breast tumour size at detection and therefore the best measures to identify women who might benefit from more intensive mammographic screening or alternative screening strategies. Setting and methods We compared the association between breast density and tumour size for 1007 screen-detected and 341 interval cancers diagnosed in an Australian mammographic screening programme between 1994 and 1996, for three semi-automated continuous measures of breast density: per cent density, dense area and dense area adjusted for non-dense area. Results After adjustment for age, hormone therapy use, family history of breast cancer and mode of detection (screen-detected or interval cancers), all measures of breast density shared a similar positive and significant association with tumour size. For example, tumours increased in size with dense area from an estimated mean 2.2 mm larger in the second quintile (β = 2.2; 95% Cl 0.4–3.9, P < 0.001) to mean 6.6 mm larger in the highest decile of dense area (β = 6.6; 95% Cl 4.4–8.9, P < 0.001), when compared with first quintile of breast density. Conclusions Of the breast density measures assessed, either dense area or per cent density are suitable measures for identifying women who might benefit from more intensive mammographic screening or alternative screening strategies.

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Screening Sensitivity According to Breast Cancer Location

Canadian Association of Radiologists Journal ◽

10.1016/j.carj.2018.10.007 ◽

2019 ◽

Vol 70 (2) ◽

pp. 186-192 ◽

Cited By ~ 1

Author(s):

Isabelle Théberge ◽

Marie-Hélène Guertin ◽

Nathalie Vandal ◽

Gary Côté ◽

Michel-Pierre Dufresne ◽

...

Keyword(s):

Breast Cancer ◽

Breast Density ◽

Central Area ◽

Lower Sensitivity ◽

Interval Cancers ◽

Experienced Radiologist ◽

Sensitivity Ratio ◽

Screening Mammograms ◽

Screening Sensitivity ◽

Adjusted Sensitivity

Purpose To examine the relation between breast cancer location and screening mammogram sensitivity, and assess whether this association is modified by body mass index (BMI) or breast density. Methods This study is based on all interval cancers (n = 481) and a random sample of screen-detected cancers (n = 481) diagnosed in Quebec Breast Cancer Screening Program participants in 2007. Film-screening mammograms, diagnostic mammograms, and ultrasound reports (when available) were requested for these cases. The breast cancer was then localised in mediolateral oblique (MLO) and craniocaudal (CC) projections of the breast by 1 experienced radiologist. The association between cancer location and screening sensitivity was assessed by logistic regression. Adjusted sensitivity and sensitivity ratios were obtained by marginal standardisation. Results A total of 369 screen-detected and 268 interval cancers could be localised in MLO and/or CC projections. The 2-year sensitivity reached 68%. Overall, sensitivity was not statistically associated with location of the cancer. However, sensitivity seems lower in MLO posterior inferior area for women with BMI ≥ 25 kg/m2 compared to sensitivity in central area for women with lower BMI (adjusted sensitivity ratio: 0.58, 95% confidence interval [CI]: 0.17–0.98). Lower sensitivity was also observed in subareolar areas for women with breast density ≥ 50% compared to the central areas for women with lower breast density (for MLO and CC projections, adjusted sensitivity ratio and 95% CI of, respectively, 0.54 [0.13–0.96] and 0.46 [0.01–0.93]). Conclusions Screening sensitivity seems lower in MLO posterior inferior area in women with higher BMI and in subareolar areas in women with higher breast density. When interpreting screening mammograms, radiologists need to pay special attention to these areas.

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Size distribution of screen-detected and interval cancers according to breast density suggests reduced screening benefit for women with higher density breasts

Breast Cancer Research ◽

10.1186/bcr833 ◽

2004 ◽

Vol 6 (S1) ◽

Author(s):

C Nickson ◽

AM Kavanagh ◽

GB Byrnes

Keyword(s):

Size Distribution ◽

Breast Density ◽

Interval Cancers

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Use of Low-Dose Tamoxifen to Increase Mammographic Screening Sensitivity in Premenopausal Women

Cancers ◽

10.3390/cancers13020302 ◽

2021 ◽

Vol 13 (2) ◽

pp. 302

Author(s):

Mikael Eriksson ◽

Kamila Czene ◽

Emily F. Conant ◽

Per Hall

Keyword(s):

Relative Density ◽

Mammographic Density ◽

Breast Density ◽

Tumor Size ◽

Low Dose ◽

Premenopausal Women ◽

Mammographic Screening ◽

Interval Cancers ◽

Dense Tissue ◽

Screening Sensitivity

Increased breast density decreases mammographic sensitivity due to masking of cancers by dense tissue. Tamoxifen exposure reduces mammographic density and, therefore, should improve screening sensitivity. We modelled how low-dose tamoxifen exposure could be used to increase mammographic sensitivity. Mammographic sensitivity was calculated using the KARMA prospective screening cohort. Two models were fitted to estimate screening sensitivity and detected tumor size based on baseline mammographic density. BI-RADS-dependent sensitivity was estimated. The results of the 2.5 mg tamoxifen arm of the KARISMA trial were used to define expected changes in mammographic density after six months exposure and to predict changes in mammographic screening sensitivity and detected tumor size. Rates of interval cancers and detection of invasive tumors were estimated for women with mammographic density relative decreases by 10–50%. In all, 517 cancers in premenopausal women were diagnosed in KARMA: 287 (56%) screen-detected and 230 (44%) interval cancers. Screening sensitivities prior to tamoxifen, were 76%, 69%, 53%, and 46% for BI-RADS density categories A, B, C, and D, respectively. After exposure to tamoxifen, modelled screening sensitivities were estimated to increase by 0% (p = 0.35), 2% (p < 0.01), 5% (p < 0.01), and 5% (p < 0.01), respectively. An estimated relative density decrease by ≥20% resulted in an estimated reduction of interval cancers by 24% (p < 0.01) and reduction in tumors >20 mm at detection by 4% (p < 0.01). Low-dose tamoxifen has the potential to increase mammographic screening sensitivity and thereby reduce the proportion of interval cancers and larger screen-detected cancers.

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965The estimated impact of improved breast screening tests targeted at women with dense breasts

International Journal of Epidemiology ◽

10.1093/ije/dyab168.546 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Pietro Procopio ◽

Louiza Velentzis ◽

A Dennis Petrie ◽

G Bruce Mann ◽

Anne M Kavanagh ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Screening ◽

Breast Cancer Screening ◽

Breast Density ◽

Screening Test ◽

Tumour Size ◽

Screening Tests ◽

Masking Effect ◽

Interval Cancers ◽

Dense Breasts

Abstract Background There is increasing interest in risk-based breast cancer screening, including interventions to improve outcomes for women with mammographically dense breasts. Methods Policy1-Breast is a continuous-time, multiple-cohort micro-simulation whole-population model which incorporates breast cancer risk, life-course breast density, menopause, hormone therapy use and screening participation. Outcomes include cancer diagnoses and characteristics (invasive/DCIS, tumour size, grade), mode of detection (screen-detected/interval/other) and mortality (breast cancer and other cause). Policy1-Breast validates well against key observed clinical outcomes in Australia. We estimate changes in outcomes within and outside the BreastScreen program upon the introduction of a hypothetical screening test with improved sensitivity for women with dense breasts. Results We estimate that introducing in year 2020 a screening test for women in the highest quintile of breast density at age 50 that halves the masking effect of their breast density would, by 2026-2030, increase diagnosis rates of population-level invasive cancers ( 10%) and screen-detected cancers (20%) and decrease rates of interval cancers (17%) and community-detected cancers (6%). Conclusions Targeted screening tests with improved sensitivity for women with dense breasts are expected to markedly reduce interval cancers and other cancers diagnosed outside the BreastScreen program, while increasing all cancer diagnoses due to increased rates of screen-detected cancers. Key messages Specialised breast cancer screening tests directed at women with very high breast density are expected to reduce interval cancers and increase overall cancer diagnoses. Population simulation models such as Policy1-Breast can complement trial evidence by evaluating a range of scenarios and estimating short and long-term implications.

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Screen-detected versus interval cancers: Effect of imaging modality and breast density in the Flemish Breast Cancer Screening Programme

European Radiology ◽

10.1007/s00330-017-4757-4 ◽

2017 ◽

Vol 27 (9) ◽

pp. 3810-3819 ◽

Cited By ~ 11

Author(s):

Lore Timmermans ◽

Luc Bleyen ◽

Klaus Bacher ◽

Koen Van Herck ◽

Kim Lemmens ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Screening ◽

Breast Cancer Screening ◽

Breast Density ◽

Screening Programme ◽

Imaging Modality ◽

Interval Cancers ◽

Breast Cancer Screening Programme ◽

Cancer Screening Programme

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Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study

British Journal of Cancer ◽

10.1038/s41416-021-01466-y ◽

2021 ◽

Author(s):

Elizabeth S. Burnside ◽

Lucy M. Warren ◽

Jonathan Myles ◽

Louise S. Wilkinson ◽

Matthew G. Wallis ◽

...

Keyword(s):

Breast Cancer ◽

Breast Density ◽

Case Control Study ◽

Case Control ◽

Imaging Biomarker ◽

Interval Cancers ◽

Node Negative ◽

Node Positive ◽

Mode Of Detection ◽

Control Study

Abstract Background 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. Methods 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. Results 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). Conclusion 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.

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