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Background: Percent density (PD) is a strong risk factor for breast cancer that is potentially modifiable by lifestyle factors. PD is a composite of the dense (DA) and nondense (NDA) areas of a mammogram, representing predominantly fibroglandular or fatty tissues, respectively. Alcohol and tobacco use have been associated with increased breast cancer risk. However, their effects on mammographic density (MD) phenotypes are poorly understood., Methods: We examined associations of alcohol and tobacco use with PD, DA, and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric. MD was measured using Cumulus. Machine-specific effects were estimated using linear regression, and combined using random effects meta-analysis., Results: Alcohol use was positively associated with PD ( P trend = 0.01), unassociated with DA ( P trend = 0.23), and inversely associated with NDA ( P trend = 0.02) adjusting for age, body mass index, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD ( P trend = 0.0008), unassociated with DA ( P trend = 0.93), and positively associated with NDA ( P trend <0.0001). These trends were stronger in normal and overweight women than in obese women., Conclusions: These findings suggest that associations of alcohol and tobacco use with PD result more from their associations with NDA than DA., Impact: PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health., (©2020 American Association for Cancer Research.)

Breast density is a modifiable factor that is strongly associated with breast cancer risk. We sought to understand the influence of newer technologies of full-field digital mammography (FFDM) on breast density research and to determine whether results are comparable across studies using FFDM and previous studies using traditional film-screen mammography. We studied 24,840 screening-age (40-74 years) non-Hispanic white women who were participants in the Research Program on Genes, Environment and Health of Kaiser Permanente Northern California and underwent screening mammography with either Hologic (Hologic, Inc., Marlborough, Massachusetts) or General Electric (General Electric Company, Boston, Massachusetts) FFDM machines between 2003 and 2013. We estimated the associations of parity, age at first birth, age at menarche, and menopausal status with percent density and dense area as measured by a single radiological technologist using Cumulus software (Canto Software, Inc., San Francisco, California). We found that associations between reproductive factors and mammographic density measured using processed FFDM images were generally similar in magnitude and direction to those from prior studies using film mammography. Estimated associations for both types of FFDM machines were in the same direction. There was some evidence of heterogeneity in the magnitude of the effect sizes by machine type, which we accounted for using random-effects meta-analysis when combining results. Our findings demonstrate the robustness of quantitative mammographic density measurements across FFDM and film mammography platforms., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: High mammographic density is strongly associated with increased breast cancer risk. Some, but not all, risk factors for breast cancer are also associated with higher mammographic density. Methods: The study cohort ( N = 24,840) was drawn from the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California and included non-Hispanic white females ages 40 to 74 years with a full-field digital mammogram (FFDM). Percent density (PD) and dense area (DA) were measured by a radiological technologist using Cumulus. The association of age at menarche and late adolescent body mass index (BMI) with PD and DA were modeled using linear regression adjusted for confounders. Results: Age at menarche and late adolescent BMI were negatively correlated. Age at menarche was positively associated with PD ( P value for trend <0.0001) and DA ( P value for trend <0.0001) in fully adjusted models. Compared with the reference category of ages 12 to 13 years at menarche, menarche at age >16 years was associated with an increase in PD of 1.47% (95% CI, 0.69-2.25) and an increase in DA of 1.59 cm 2 (95% CI, 0.48-2.70). Late adolescent BMI was inversely associated with PD ( P < 0.0001) and DA ( P < 0.0001) in fully adjusted models. Conclusions: Age at menarche and late adolescent BMI are both associated with Cumulus measures of mammographic density on processed FFDM images. Impact: Age at menarche and late adolescent BMI may act through different pathways. The long-term effects of age at menarche on cancer risk may be mediated through factors besides mammographic density. Cancer Epidemiol Biomarkers Prev; 26(9); 1450-8. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Background: Breast-conserving surgery (BCS) is the most common treatment for ductal carcinoma in situ (DCIS); however, how often women experience subsequent diagnostic evaluations over time is not known., Methods: We identified 2948 women with DCIS who were treated with BCS from 1990 to 2001 and followed for up to 10 years at three integrated health-care delivery systems. We calculated the percentages of diagnostic mammograms and ipsilateral invasive procedures following the initial breast excision to treat DCIS, estimated the 10-year cumulative incidence of these procedures, and determined hazard ratios for both types of procedures with Cox regression modeling. All statistical tests were two-sided., Results: Over 10 years, 907 women (30.8%) had 1422 diagnostic mammograms and 1813 (61.5%) had 2305 ipsilateral invasive procedures. Diagnostic mammograms occurred in 7.3% of women in the first 6 months and continued at a median annual rate of 4.3%. Ipsilateral invasive procedures occurred in 51.5% of women in the first 6 months and continued at a median annual rate of 3.1%. The estimated 10-year cumulative risk of having at least one diagnostic mammogram after initial DCIS excision was 41.0% (95% confidence interval [CI] = 38.5% to 43.5%); at least one invasive procedure, 65.7% (95% CI = 63.7% to 67.8%); and either event, 76.1% (95% CI = 74.1% to 78.1%). Excluding events in the first 6 months following initial DCIS excision, corresponding risks were 36.4% (95% CI = 33.8% to 39.0%) for diagnostic mammograms, 30.4% (95% CI = 26.9% to 33.8%) for invasive procedures, and 49.5% (95% CI = 45.6% to 53.5%) for either event., Conclusions: Women with DCIS treated with BCS continue to have diagnostic and invasive breast procedures in the conserved breast over an extended period. The frequency of ongoing diagnostic breast evaluations should be included in discussions about treatment.

PURPOSE Breast-conserving surgery (BCS) is an effective treatment for ductal carcinoma in situ (DCIS) but women who undergo BCS remain at risk for recurrences. Whether mammographic surveillance after BCS occurs and by whom is not known. METHODS We reviewed medical records of women diagnosed with DCIS between 1990 and 2001 and treated with BCS. Using descriptive statistics, generalized estimating, and logistic regression modeling, we examined the rates and predictors of surveillance mammography over a 10-year period after BCS. Results The cohort included 3,037 women observed for a median of 4.8 years (range, 0.5 to 15.7). Of the 2,676 women observed for at least 1 year after BCS, most (79%) had at least one surveillance mammogram during the first year of follow-up; 69% in year 5 and 61% in year 10. Among those observed for 5 years, surveillance mammograms were more likely among women age 60 to 69 years (odds ratio [OR], 1.72; 95% CI, 1.26 to 2.34), users of menopausal hormone therapy at diagnosis (OR, 1.26; 95% CI, 1.01 to 1.57) as well as those treated with adjuvant radiation (OR, 1.28; 95% CI, 1.08 to 1.53) and adjuvant radiation with tamoxifen (OR, 1.61; 95% CI, 1.13 to 2.30). Surveillance mammograms were less likely among obese women (OR, 0.70; 95% CI, 0.56 to 0.86). The findings were similar among women observed for 10 years. Only 34% and 15% of women observed for 5 and 10 years, respectively, had a surveillance mammogram during each year of follow-up. CONCLUSION Surveillance mammography after BCS among insured women with DCIS often did not occur yearly and declined over time after treatment. Patients and providers must remain vigilant about surveillance after BCS.

Background Although several clinical breast cancer risk models are used to guide screening and prevention, they have only moderate discrimination. Purpose To compare selected existing mammography artificial intelligence (AI) algorithms and the Breast Cancer Surveillance Consortium (BCSC) risk model for prediction of 5-year risk. Materials and Methods This retrospective case-cohort study included data in women with a negative screening mammographic examination (no visible evidence of cancer) in 2016, who were followed until 2021 at Kaiser Permanente Northern California. Women with prior breast cancer or a highly penetrant gene mutation were excluded. Of the 324 009 eligible women, a random subcohort was selected, regardless of cancer status, to which all additional patients with breast cancer were added. The index screening mammographic examination was used as input for five AI algorithms to generate continuous scores that were compared with the BCSC clinical risk score. Risk estimates for incident breast cancer 0 to 5 years after the initial mammographic examination were calculated using a time-dependent area under the receiver operating characteristic curve (AUC). Results The subcohort included 13 628 patients, of whom 193 had incident cancer. Incident cancers in eligible patients (additional 4391 of 324 009) were also included. For incident cancers at 0 to 5 years, the time-dependent AUC for BCSC was 0.61 (95% CI: 0.60, 0.62). AI algorithms had higher time-dependent AUCs than did BCSC, ranging from 0.63 to 0.67 (Bonferroni-adjusted P < .0016). Time-dependent AUCs for combined BCSC and AI models were slightly higher than AI alone (AI with BCSC time-dependent AUC range, 0.66-0.68; Bonferroni-adjusted P < .0016). Conclusion When using a negative screening examination, AI algorithms performed better than the BCSC risk model for predicting breast cancer risk at 0 to 5 years. Combined AI and BCSC models further improved prediction. © RSNA, 2023 Supplemental material is available for this article.

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P

Background: Full-field digital mammography (FFDM) has largely replaced film-screen mammography in the US. Breast density assessed from film mammograms is strongly associated with breast cancer risk, but data are limited for processed FFDM images used for clinical care.Methods: We conducted a case-control study nested among non-Hispanic white female participants of the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California who were aged 40 to 74 years and had screening mammograms acquired on Hologic FFDM machines. Cases (n = 297) were women with a first invasive breast cancer diagnosed after a screening FFDM. For each case, up to five controls (n = 1149) were selected, matched on age and year of FFDM and image batch number, and who were still under follow-up and without a history of breast cancer at the age of diagnosis of the matched case. Percent density (PD) and dense area (DA) were assessed by a radiological technologist using Cumulus. Conditional logistic regression was used to estimate odds ratios (ORs) for breast cancer associated with PD and DA, modeled continuously in standard deviation (SD) increments and categorically in quintiles, after adjusting for body mass index, parity, first-degree family history of breast cancer, breast area, and menopausal hormone use.Results: Median intra-reader reproducibility was high with a Pearson's r of 0.956 (range 0.902 to 0.983) for replicate PD measurements across 23 image batches. The overall mean was 20.02 (SD, 14.61) for PD and 27.63 cm(2) (18.22 cm(2)) for DA. The adjusted ORs for breast cancer associated with each SD increment were 1.70 (95 % confidence interval, 1.41-2.04) for PD, and 1.54 (1.34-1.77) for DA. The adjusted ORs for each quintile were: 1.00 (ref.), 1.49 (0.91-2.45), 2.57 (1.54-4.30), 3.22 (1.91-5.43), 4.88 (2.78-8.55) for PD, and 1.00 (ref.), 1.43 (0.85-2.40), 2.53 (1.53-4.19), 2.85 (1.73-4.69), 3.48 (2.14-5.65) for DA.Conclusions: PD and DA measured using Cumulus on processed FFDM images are positively associated with breast cancer risk, with similar magnitudes of association as previously reported for film-screen mammograms. Processed digital mammograms acquired for routine clinical care in a general practice setting are suitable for breast density and cancer research. [ABSTRACT FROM AUTHOR]