Cross-sectional study to assess the association of population density with predicted breast cancer risk.

Background - There is suggestive evidence of familial clustering of breast and prostate cancer in first-degree relatives; women with a family history of prostate cancer are at increased risk of breast cancer. Few studies have investigated joint family history of breast and prostate cancer and prostate cancer risk, and no study to date has examined lethal prostate cancer. Methods - We studied 42,672 from the Health Professionals Follow-up Study between 1996 to 2012. During follow-up, 4,258 prostate cancer cases were diagnosed, of whom 380 were lethal disease. Men self-reported family history of breast and prostate cancer, including in siblings or parents. Using cause-specific hazards regression, we estimated hazard ratios (HR) and 95% confidence intervals (CI) of the association between family history and prostate cancer risk and progression. Results - About 8% of men had a family history of prostate cancer, 8.7% had a family history of breast cancer, and 1.4% of men had a family history of both breast and prostate cancer. A family history of prostate cancer was significantly associated with an increased risk of prostate cancer (HR: 1.69; 95% CI: 1.54-1.85). Increased risk was higher for men with a father diagnosed with prostate cancer (HR: 1.64 95% CI: 1.49-1.80) than for men with a diagnosis in a brother(s) (HR: 1.51 95% CI: 1.27-1.80). A positive family history of breast cancer was associated with a small, but significant 22% increased risk (HR: 1.22; 95% CI: 1.11-1.35). Familial breast cancer in a sister (HR: 1.22 95% CI: 1.06-1.41) increased risk more than familial breast cancer in a mother (HR: 1.12; 95% CI: 0.99-1.25). Men with a family history of both prostate and breast cancer had a 52% (HR: 1.52; 95%CI: 1.23-1.88) increased risk of prostate cancer compared to men with no family history of either cancer. Risk of lethal prostate cancer was also significantly increased for men with a positive family history of prostate cancer (HR: 1.64; 95% CI: 1.20-2.24), as well as for men with a family history of breast cancer (HR: 1.47; 95% CI: 1.07-2.01). Conclusions - These results support the findings of familial aggregation of breast and prostate cancer, and for the first time suggest an association between familial breast cancer and lethal prostate cancer. Data from this prospective study have translational relevance for family counseling of cancer patients. Citation Format: Lauren E. Barber, Travis A. Gerke, Sarah C. Markt, Giovanni Parmigiani, Lorelei A. Mucci. A family affair: Prostate cancer risk and family history of breast or prostate cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2543.

Providers Respond to USPSTF Report on Screening for Breast Cancer

Background: Accurate assessment of a woman’s individualized breast cancer risk is necessary to inform shared decision-making regarding screening and risk-reducing strategies. Recently, deep learning techniques, including convolutional neural networks (CNN), have shown better predictive potential for breast cancer risk compared to mammographic density (MD). We evaluated whether combining clinical factors in the Breast Cancer Surveillance Consortium (BCSC) model, including MD, with a novel CNN-based mammographic evaluation more accurately predicts breast cancer risk than the BCSC model alone in a cohort of racially/ethnically diverse women. Methods: We conducted a retrospective cohort study of 23,552 women, age 35-74 years, who underwent screening mammography from 2014 to 2018 at Columbia University Irving Medical Center in New York City. We extracted data from the electronic health record (EHR) on breast cancer risk factors (age, race/ethnicity, prior benign breast biopsy, first degree family history of breast cancer, and MD). From this cohort, we identified 206 women who developed breast cancer by linkage to the tumor registry. We calculated 5-year invasive breast cancer risk using the BCSC model. We applied CNN-based breast cancer risk model to full-field craniocaudal mammographic views of both breasts, with an output of a risk score (range, 0-1). We used logistic regression models with breast cancer status as the outcome and predictors including clinical factors only (BCSC model) or combined with CNN risk score (hybrid model). We compared the prediction performance of these models via area under the receiver operating characteristics curves (AUCs) based on the DeLong test. We also calculated each model’s AUC for subgroups of age and race/ethnicity. Results: Among 23,552 evaluable women, mean age was 55.9 years (standard deviation [SD], 9.5) with 27% non-Hispanic White, 9% non-Hispanic Black, 36% Hispanic, 5% Asian, and 23% Other/Unknown race/ethnicity. Four percent had a first-degree family history of breast cancer, 10% had a prior benign breast biopsy, 45% had heterogeneously or extremely dense breasts on mammography, and 22% met high-risk criteria based upon a 5-year invasive breast cancer risk 1.67% according to the BCSC model. Mean CNN risk score was higher among breast cancer cases compared to unaffected controls (0.477 vs. 0.466, p=0.077). We found that the hybrid model outperformed the BCSC model (AUC of 0.676 vs. 0.640, respectively; p=0.003). In subgroup analyses, the hybrid model more accurately predicted breast cancer risk compared to the BCSC model among women age<50 (AUC of 0.713 vs. 0.645, respectively; p=0.078) and age>=50 (AUC of 0.663 vs. 0.625, respectively; p=0.026); non-Hispanic Black women (AUC of 0.794 vs. 0.663, respectively; p=0.028) and Hispanic women (AUC of 0.666 vs. 0.621, respectively; p=0.060). Conclusion: Among women undergoing screening mammography, a hybrid model incorporating a CNN-based mammography evaluation with clinical factors from the BCSC model more accurately predicted breast cancer risk relative to the BCSC model alone, particularly among racial and ethnic minorities. Combined with clinical risk factors, our CNN model may be used to efficiently predict breast cancer risk and inform risk-stratified breast cancer screening and prevention strategies. Comparing prediction performance for breast cancer risk of the BCSC model vs. hybrid modelBCSC ModelHybrid ModelP-value*AUC95% CIAUC95% CIAll patients0.6400.602-0.6830.6760.640-0.7110.003Age (years)<500.6450.562-0.7280.7130.648-0.7780.078>=500.6250.579-0.6710.6630.623-0.7030.026Race/ethnicityNon-Hispanic White0.6880.623-0.7540.7040.643-0.7660.230Non-Hispanic Black0.6630.539-0.7880.7940.704-0.8830.028Hispanic0.6210.560-0.6860.6660.597-0.7330.060Asian0.6160.440-0.7910.6510.461-0.8410.694 Citation Format: Alissa Michel, Vicky Ro, Julia E McGuinness, Simukayi Mutasa, Richard Ha, Katherine D Crew. Improving breast cancer risk prediction using a convolutional neural network-based mammographic evaluation in combination with clinical risk factors [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-10-03.

To the Editor, Breast-Cancer Risk in Families with Mutations in PALB2: A.C. Antoniou, S. Casadei, T. Heikkinen, et al. N Engl J Med. 2014;371:497-506. In a study published in N Engl J Med. August 2014, researchers from 14 centers in eight countries investigated information from 362 family members from 154 families who had an abnormal partner and localizer of BRCA2 (PALB2) gene, but did not have an abnormal BRCA1 or BRCA2 gene. Their aim was to demonstrate the importance of loss-of-function mutations in PALB2 as a cause of hereditary breast cancer. The study included 311 women with an abnormal PALB2 gene; 229 of these women had been diagnosed with breast cancer and 51 men with an abnormal PALB2 gene; seven of whom had been diagnosed with breast cancer. The researchers compared the breast cancer risk of the study population to the general population. They found out that overall, women with an abnormal PALB2 gene had a risk of breast cancer that was 9.47 times higher than average. Women with an abnormal PALB2 gene had a 14% risk of developing breast cancer by age 50 and a 35% risk of developing breast cancer by age 70. The average lifetime risk of breast cancer is about 12%. This increase in risk linked to an abnormal PALB2 gene was dependent on the women’s age and family history. They have demonstrated that the relative risk of breast cancer among PALB2 mutation carriers increased significantly as birth cohort became more recent (P<0.001). In women with an abnormal PALB2 gene, breast cancer risk was eight to nine times higher than average in women aged 20 to 39, six to eight times higher than average in women aged 40 to 60, and five times higher than average in women older than 60 years of age. By the age of 70, women with an abnormal PALB2 gene with no family history of breast cancer had a 33% risk of developing breast cancer whereas women with two or more first-degree relatives with breast cancer at 50 years of age had a 58% risk of developing the disease. The authors concluded that based on their estimates, breast cancer risk for a PALB2 mutation carrier, even in the absence of a family history of breast cancer, would be classified as high according to various guidelines. The researchers also reported that this level of risk may justify adding PALB2 to genetic testing for BRCA1 and BRCA2. A Genetic counselor’s perspective Partner and localizer of BRCA2 (PALB) is a gene whose protein facilitates the function of BRCA2 and interacts with BRCA1 to aid in repairing double strand and interstrand cross-link DNA damage. Biallelic PALB2 mutations cause Fanconi Anemia complement group N (FANCN) and monoallellic mutations in the PALB2 gene are associated with increased breast and pancreas cancer risks (1). PALB2 mutations may account for as much as 3% of familial breast cancer risk (2). A recent study of 362 members from PALB2 mutation positive families found that the risk for breast cancer in female mutation carriers ranged between 33% to 58% by age 70, with the higher risks relating to those women with a family history of early onset (<50) breast cancer in 2 first degree family members (3). The study also identified an 8 fold increase in male breast cancer risk and a 2 fold increase in ovarian cancer risk, both of which need to be confirmed in additional studies due a lack of statistical significance. These data suggest that female PALB2 mutation carriers may have breast cancer risks that are similar to those conferred by mutations in the BRCA2 gene. These findings suggest that women who carry PALB2 gene mutations may warrant similar breast cancer screening and prevention strategies as those offered to BRCA2 mutation carriers. PALB2 mutation analysis is available and is rapidly being adopted into clinical practice. As the data continues to accumulate it is likely that PALB2 mutation analysis will become a standard part of genetic testing in the realm of hereditary breast cancer predisposition. Whether testing will be done in addition to BRCA1/2 or as part of a larger breast cancer gene panel remains to be determined. In addition, more data will provide evidence to support the development of specific management guidelines to aid in the care of these at risk patients.

Purpose: Breast biopsies with benign findings (benign breast disease [BBD]) outnumber biopsies revealing in-situ or invasive cancer 4:1, providing an opportunity to identify histopathological features that predict breast cancer risk. Greater degrees of involution of terminal duct lobular units (TDLUs), the structures within the breast that produce milk and the primary source of breast cancer precursors, have been inversely associated with breast cancer risk among women with BBD. We recently developed measures to quantitate levels of TDLU involution, which demonstrate high inter/intra pathologist reproducibility. Here we assessed whether TDLU counts/100mm2 and median TDLU span (microns), two measures inversely related to degree of TDLU involution, are associated with subsequent breast cancer risk among women with BBD. Methods: From the Mayo BBD cohort (n = 9,376), we evaluated benign biopsies from 99 women who later developed breast cancer (cases) and 145 age-matched controls who did not develop breast cancer. Digitized images of biopsy sections were reviewed to enumerate TDLUs/mm2 and measure median TDLU span (microns) for up to ten normal TDLUs. Breast cancer risk factors were available from questionnaires or medical records. To assess associations with breast cancer risk, subjects were categorized into quartile levels of TDLU counts and median TDLU spans, based on data from controls. Odds ratios (ORs) and 95% confidence intervals (CI) were estimated using multivariable conditional logistic regression models, adjusted for histologic type of BBD, family history of breast cancer and menopausal hormone use. Results: Compared to controls, women who developed breast cancer had higher median number of TDLU counts/100mm2 (28 vs 20, p = 0.03) and larger TDLU spans (300 vs 267 microns, p = 0.14). In multivariable models higher TDLU counts (quartile4 vs. quartile1, OR = 2.44, 95%CI = 0.96-6.19, ptrend = 0.02) and larger TDLU span measures (quartile4 vs. quartile1, OR = 2.83, 95%CI = 1.13-7.06, ptrend = 0.03) were associated with subsequent diagnosis of breast cancer. Combinatorial metrics of TDLU counts with median TDLU span measures identified women at higher risk; specifically, women above the median for both TDLU span and TDLU counts had an OR = 3.75 (95%CI = 1.40-10.00, ptrend = 0.008), compared with women below the median for TDLU span and TDLU counts. Conclusion: These data show that lack of TDLU involution, as measured by increased persistence of TDLU counts, larger median TDLU spans and cross-classification using these measures was associated with increased breast cancer risk among women with BBD, extending prior work in this cohort based on other TDLU involution metrics. Future studies to identify determinants of TDLU involution, its association with breast cancer risk and its potential as an intermediate endpoint in prevention studies warrant consideration. Citation Format: Jonine D. Figueroa, Ruth Pfeiffer, Maya Palakal, Amy C. Degnim, Derek Radisky, Lynn C. Hartmann, Marlene Frost, Melody L. Stallings Mann, Louise A. Brinton, Daphne Papathomas, Daniel Visscher, Mark E. Sherman. Standardized measures of lobular involution and subsequent breast cancer risk among women with benign breast disease. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4682. doi:10.1158/1538-7445.AM2015-4682

Background: Established risk factors for breast cancer (BC) only explain 25% to 47% of BC incidence. The Gail model is commonly used to assess BC risk and determine eligibility for prevention trials. Unfortunately, it has a discriminatory accuracy of 58% at the individual level. A greater understanding of BC risk factors is needed to offer improved risk stratification and prevention. It is plausible that BC risk may be related to deficiencies or abnormalities in DNA repair and cell cycle checkpoints because of their importance in maintaining genomic integrity. Recent epidemiologic studies support this hypothesis. In this pilot project, the bleomycin mutagen sensitivity assay (MSS), a measure of genetic susceptibility was performed on women of low, intermediate, and high risk based on commonly used risk models to determine if there was any correlation between MSS and established BC risk factors.Methods: Women in the Prevention Clinic at RPCI consented to donate blood for this study as part of the Data Bank and BioRepository (DBBR). Gail and Claus Models were calculated using CancerGene. Women were stratified into three groups low (&amp;lt;20%), intermediate (20%-35%), and high (&amp;gt; 35%) lifetime BC risk. For logistic regression analysis, women were grouped into low risk (&amp;lt;20%) and high risk (≥20%). MSS in blood lymphocytes were performed at LCCC using fresh blood samples. The mean values of MSS were compared between low, intermediate, and high risk groups using Wilcoxon-Mann-Whitney tests. Multivariate logistic regression was used to analyze the relationship between BC risk groups and MSS.Results: A total of 78 women were enrolled in the study. MSS were performed on 70 blood samples and 67 had evaluable slides. There were 30, 26 and 11 women in the low, intermediate, and high risk groups respectively. The mean age was 49.1 years. There was no statistical difference between the three groups with respect to age, race, menopausal status, proportion of patients with a family history of BC or another cancer, and smoking status (never, former, or current). The mean MSS score was not significantly different among the three risk groups: mean ±SD = 0.86±0.37, 0.84±0.37 (p=0.565), and 0.76+0.44 (0.361) for low, intermediate and high risk groups respectively. Spearman correlation revealed that MSS score did not correlate with Gail lifetime BC risk score (r=-0.054, p=0.668) or Claus model-10 year risk score (r=-0.057, p=0.722). Using the median in low risk women as a cut point, when women who had higher MSS score were compared with women had lower MSS score, the adjusted OR was 1.16 (95% CI, 0.29 to 4.57), adjusted for age, race, smoking status, BMI and menopausal status. When the MSS score were categorized into quartiles, no significant dose-response relationship was observed.Conclusions: In this pilot study, there was no correlation between commonly used breast cancer risk assessment models based on hormonal, family and biopsy history and the MSS in our study population. Previous case-control studies have consistently shown that MSS is significantly associated with BC risk. The lack of correlation between mutagen sensitivity and Gail or Claus risk score suggests that mutagen sensitivity may measure the host susceptibility factors that are not considered by Gail or Claus risk models. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6067.

Introduction: Multiple risk factors for postmenopausal breast cancer are well established. We aimed to determine the proportion of breast cancers in the population that are attributable to established risk factors, and to different combinations of risk factors, to better understand the proportion of breast cancer which could be prevented by changes in modifiable risk factors. Methods: We used data from the Nurses' Health Study (NHS), an ongoing prospective study of 121,700 US nurses initiated in 1976. Information on breast cancer risk factors and breast cancer diagnosis is collected every two years through mailed questionnaires. Follow-up for this cohort of women through 2008 has been greater than 90%. The analysis was restricted to postmenopausal women. Relative risks and their 95% confidence intervals were estimated by Cox models stratified by calendar year and age in months at the time of each questionnaire return using the counting process data structure to facilitate the incorporation of time-varying covariates. We included the following established breast cancer risk factors in the analyses: age, age at menarche, height, age at first birth/parity, current adult BMI/weight change since age 18, alcohol consumption, physical activity, breast feeding, menopausal hormone therapy, family history of breast cancer, and prior benign breast disease. Full and partial population attributable risk percents (PARs) were calculated. We conducted analyses for total invasive breast cancer, estrogen receptor (ER)+, and ER- breast cancer. Results: Over the course of follow-up, 8,421 postmenopausal invasive breast cancer cases developed over 2,424,778 person years between 1980 and 2008. As expected, earlier age at menarche, increasing weight gain since age 18, increasing alcohol consumption, current use of menopausal hormones, and being tall were all significantly positively associated with risk of breast cancer in multivariate models. Because age has a large influence on the risk of breast cancer we estimated the PAR both with and without age. When all of the risk factor variables except for age were include in the model the PAR for all invasive breast cancers was 0.62 (95% CI 0.46-0.75). Thus, if women could change to the lowest risk category for all of the variables considered, the number of invasive breast cancers would be reduced by 62%. In models that additionally included age, the PAR was 0.92 (95%CI 0.76-0.97) for total invasive and 0.95 (95%CI 0.75-0.99) for ER+ breast cancer and 0.86 (95%CI 0.21-0.98) for ER- breast cancer. However, because many of the risk factors considered are not easily modifiable, we also examined more readily modifiable risk factors singly and in combinations. The risk factor with the largest PAR, was BMI/weight gain since age 18 (PAR=0.24(95%CI 0.13-0.34)). Reproductive risk factors such as age at first birth/parity (PAR=0.10 (95%CI 0.07-0.14)) and age at menarche (PAR=0.08 (95%CI 0.03-0.12)) also had modest impact on the PAR, both of which were higher for ER+ breast cancer than ER- breast cancer. When considering all of the modifiable risk factors together we found that changing one's risk factor profile to have the lowest weight gain, no alcohol consumption, high physical activity, breast feeding and no hormone use was associated with a PAR of 0.38 (95%CI 0.23-0.52) for overall invasive breast cancer. Conclusion: The established breast cancer risk factors explain a large proportion of both ER+ and ER- postmenopausal breast cancers in the population. The most important modifiable risk factor for postmenopausal breast cancer prevention is maintaining a healthy weight. Citation Format: Rulla M. Tamimi, Molin Wang, Mathew Pazzaris, Stephanie A. Smith-Warner, Walter C. Willett, A. Heather Eliassen, Donna Spiegelman, David J. Hunter. Population attributable risk of postmenopausal breast cancer according to known and modifiable breast cancer risk factors. [abstract]. In: Proceedings of the Thirteenth Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2014 Sep 27-Oct 1; New Orleans, LA. Philadelphia (PA): AACR; Can Prev Res 2015;8(10 Suppl): Abstract nr A43.

Race and Reproductive Coercion: A Qualitative Assessment

Background: The risk of breast cancer is at least doubled in young women with a family history of breast cancer. Pregnancy has a dual effect on breast cancer risk; a short-term increase followed by a long-term protection. It has been hypothesized that women with a genetic predisposition for breast cancer are particularly susceptible to physiological changes during childbearing that may influence short term risk. Materials &amp; methods: We followed a cohort of women aged 15 to 44 years between 1963 and 2009 identified in Swedish registers. Family history was defined as having a mother or sister with breast cancer. In a case-cohort analysis, we estimated incidence rate ratios of breast cancer during pregnancy and time intervals up to 10 years post-delivery. Results: In 3,452,506 women, there were 15,548 cases of breast cancer (1,208 were pregnancy-associated (PABC), defined as breast cancer during or within 2 years of pregnancy). Compared to nulliparous women, the risk of breast cancer was decreased during pregnancy, similar during 1st year and increased during 2nd year post-delivery. The pattern was similar in women with or without family history of breast cancer. A peak in risk was observed 5-6 years following the first birth regardless of family history. After a second birth, this peak was only present in women with a family history. Conclusions: Our results indicate that women with a family history of breast cancer do not have a different breast cancer risk during and within 10 years following pregnancy compared to women without a family history. Citation Format: Lambe M, Johansson ALV, Andersson TM, Hsieh C-C, Cnattingius S, Dickman PW. Family history and risk of pregnancy-associated breast cancer (PABC). [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-10-07.

Background: The Gail breast cancer risk assessment model takes into account the relative contribution of various breast cancer risk factors (RF) and provides 5-year and lifetime breast cancer risk estimates. The purpose of this analysis was to determine the relative contribution of the Gail model RF in patients with and without family history of breast cancer (FHBC).Materials and Methods: Patients from the RUTH trial, consisting of postmenopausal women with or at high risk for coronary artery disease (CAD), were included in this analysis, with the exception of women ≥86 years of age or with medical history of any breast cancer, ductal carcinoma in situ, or lobular carcinoma in situ. Patients with missing values for RF were also excluded. For the resulting study population (N=10015), the risk score was calculated using the breast cancer risk assessment (BCRA) tool from the National Cancer Institute. A descriptive analysis of the BCRA risk scores for each RF stratified based on the presence or absence of a FHBC was performed. Risk factors were categorized as follows: advancing age (&amp;lt;65 or ≥65; 65 was the mean age); age at menarche (&amp;gt;12 or ≤12), number of biopsies (None or ≥1), age at first live child birth (&amp;lt;30 or ≥30; nulliparty included in &amp;lt;30 group per model). Interaction plots based on the two-way analysis of variance (ANOVA) model were generated for each category of the RF.Results: Of the 10015 women, 9123 (91.1%) did not have FHBC, while 892 (8.9%) did. Among women without FHBC, the mean BCRA score (%) was 1.54±0.40; 62.2% were 65 years or older, 28.8% had early menarche, 8.4% had first child at ≥30 years of age, and 8.1% had a previous breast biopsy. Among women with FHBC, mean BCRA score was 3.46±1.24; 70.3% were 65 years or older, 30.4% had early menarche, 9.3% had first child at ≥30 years of age, and 15.4 % had a previous breast biopsy. A statistically significant (p&amp;lt;0.001) amplification in the risk conferred by advancing age, previous biopsy, and early menarche was observed in patients with FHBC compared with patients with no family history for the disease (Figure 1). In contrast, the relative contribution to risk by late childbearing is more pronounced (p&amp;lt;0.001) in patients without FHBC.Discussion: Family history is an independent and important determinant of breast cancer risk in postmenopausal women. Other RF have a different influence on the overall risk estimate in women with FHBC when compared to women without FHBC. Increased risk was observed for advancing age, early menarche, and previous breast biopsy. A different pattern was seen for late childbearing. While the data were obtained from a large cohort of women, further analysis may be required to determine if these results are generalizable for all women regardless of menopausal status or CAD.Figure 1. Mean BCRA risk within each risk factor group, stratified by FHBC. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6062.

9677 Background: Mammographic density (MD) is a known risk factor for breast cancer and demonstrates heritability. Germline BRCA1/2 mutation-carriers are at markedly increased lifetime risk for breast cancer, but providing a personalized risk estimate for breast cancer is problematic. We investigated MD of BRCA1/2 mutation-carriers to determine (1) if it can predict for BRCA1/2 mutation status and (2) if it is an independent risk factor for breast cancer. Methods: Mammograms were collected from a cross section of germline BRCA1/2 mutation-carriers both affected (Pos Aff) and unaffected (Pos Unaff) by breast cancer and from women negative for a known familial BRCA1/2 mutation (Negs). MD was scored using the Wolfe and Boyd six category classification (SCC) systems and a computer-assisted thresholding algorithm. Odds ratios (ORs) for the effect of MD on the presence of a BRCA1/2 mutation or breast cancer risk were estimated using unconditional logistic regression, using the least dense categories as reference categories for each classification system. ORs were compared using the X2 test for trend with increasing density. Results: In the pilot phase, MD was scored for 34 Pos Aff, 21 Pos Unaff, 33 Negs. For both Wolfe and Boyd SCC systems, a statistically significant difference in density between the Pos Aff and Pos Unaff groups was observed (P=0.034 and 0.043 respectively) with a trend to increased density in the Pos Aff group. No difference in density was observed between mutation-carriers and non-carriers. Mammograms from a further 74 Pos Aff, 117 Pos Unaff and 129 Negs have been located, digitised and scored using all the classification systems and the final analysis will be complete by ASCO 2005. Conclusions: In the pilot phase MD is greater in BRCA1/2 mutation-carriers affected by breast cancer and merits further investigation to investigate potential clinical applications for personalising breast cancer risk estimates and selection of appropriate risk management strategies. MD does not appear to be predictive for BRCA1/2 mutation status suggesting that the reported heritability of mammographic density is associated with genes other than BRCA1/2. No significant financial relationships to disclose.

The relationship between family history of breast, ovarian and endometrial cancer and risk of breast cancer was analysed using data from a case-control study of breast cancer conducted in the greater Milan area, Northern Italy. The cases studied were 3415 women (median age 52 years, range 23-74) who had histologically confirmed breast cancer diagnosed within the year preceding the interview. The controls were 2916 women (median age 54 years; range 21-74) in hospital for a spectrum of acute illnesses excluding gynaecological, hormonal or neoplastic conditions. A total of 375 cases (11.0%) and 128 controls (4.4%) reported a history of breast cancer in first degree relatives. Compared with women with no family history of breast cancer, the RR was 2.7 (95% confidence interval [CI] : 2.2-3.3) in those with one first degree relative affected and 2.8 (95% CI : 1.3-5.7) in those with two or more affected relatives. In comparison with women without family history of ovarian cancer the RR of breast cancer was 1.4 (95% CI : 0.9-2.3) for those reporting one or more first degree relatives with ovarian cancer. However, the multivariate estimate for family history of ovarian cancer, including a term for familial breast cancer, decreased to 0.8 (95% CI : 0.5-1.4). The risk of breast cancer was similar in women reporting a family history of breast cancer (RR = 2.2) and in those reporting a family history of both breast and ovarian cancer (RR = 2.5), in comparison with women reporting no family history of breast and/or ovarian cancer.(ABSTRACT TRUNCATED AT 250 WORDS)

Introduction: Giving birth may be associated with a transient increase in breast cancer risk post-delivery and with elevated risk of basal breast cancers, especially in the absence of breastfeeding, whereas parity is related to lower risk of postmenopausal ER-positive tumors. Black women develop more early-onset and basal breast cancers than White women, but factors contributing to this disparity are poorly understood. Accordingly, we compared levels of 15 proteins with hypothesized roles in breast cancer risk in breastmilk from healthy Black and White women. Methods: We tested breastmilk donated by 130 Black and 162 White women, annotated with breast cancer risk factor questionnaire data. Following pilot testing using the MesoScale Discovery system (Rockville, MD), the following analytes were measured in breastmilk, adjusted for total protein concentration: interferon-γ, IL1-β, IL-6, IL-8, TNF-α, FLT-1, TIE-2, PlGF, VEGFC, VEGFD, adiponectin, leptin, and FAS-L. M30-apoptosis and Bradford protein were measured with Molecular Devices VersaMax reader (Sunnyvale, CA). Univariate associations of race with women's characteristics were computed using chi square tests and t-tests. Multivariable logistic regression models with a random effect to account for plate effects were used to assess the associations (odds ratios (ORs) and 95% confidence intervals (CIs)) of analyte levels with: race, family history of breast cancer, smoking, baby's age in days, body mass index at time of sample donation, age, menarche, age at first birth, return of menses, parity, and over-the-counter pain medication. Results: Of the 15 analytes measured, all but VEGFC and TIE2 were detectable and reliably measured. Black women compared to White women had higher BMI (p = 0.05) and higher parity (p = 0.02), and were younger age at menarche (p = 0.005) and younger age at first birth (p = 0.01). White women had higher levels of smoking (p = 0.01) and more frequently had a first degree relative with breast cancer (p = 0.03). Compared with White women, Black women had significantly higher levels of IL1-β (OR 1.77, 95% CI 1.13 - 2.77, p = 0.01) adjusting for the baby's age in days. Black women had significantly higher levels of leptin (OR 2.01, 95% CI 1.28 - 3.15, p = 0.002) and leptin/adiponectin ratio (OR 2.36, 95% CI 1.49 - 3.72, p = 0.0004), even after adjusting for body mass index. Discussion: Preliminary data demonstrate differences in levels of putative markers of breast cancer risk between White and Black women, including IL1-β, leptin and the leptin/adiponectin ratio. These data suggest that further analyses of biomarkers in breastmilk may be useful for understanding breast cancer risk and to identify possible factors that may be associated with racial disparities in early onset and basal breast cancers. Citation Format: Jeanne Murphy, Mark E. Sherman, Ruth M. Pfeiffer, Hannah P. Yang, Ana I. Caballero, Eva P. Browne, Gretchen L. Gierach, Kathleen F. Arcaro. Cytokines and adipokines in breastmilk of black and white women. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4298.

Expanding access to genetic testing and availability of validated breast cancer (BC) risk prediction models are increasingly identifying women at elevated BC risk who do not carry high-penetrance BRCA1/BRCA2/PALB2 pathogenic variants. The precise BC risk threshold for offering risk-reducing mastectomy (RRM) for BC prevention is unknown. To define the lifetime BC risk thresholds for RRM to be cost-effective compared with nonsurgical alternatives for BC prevention. This economic evaluation used a decision-analytic Markov model to compare the cost-effectiveness of RRM with BC screening and medical prevention in a simulated cohort. Extensive sensitivity analyses were performed. The study setting was from a UK payer perspective over a lifetime horizon until age 80 years. The simulated cohort included women aged 30 to 60 years at varying lifetime BC risks from 17% to 50%. The study was conducted between September 2022 and September 2024. Undergoing RRM or receiving risk-stratified BC screening with medical prevention (tamoxifen or anastrozole). The incremental cost-effectiveness ratio was calculated as incremental cost per quality-adjusted life-year (QALY) gained and compared with the UK willingness-to-pay (WTP) threshold of £20 000 (US $27 037) to £30 000 (US $40 555) per QALY. BC cases prevented were estimated at the population level. In the simulated cohort of 100 000 thirty-year-old women in the UK, undergoing RRM became cost-effective at a 34% lifetime BC risk using the £30 000 (US $40 555) per QALY WTP threshold. This increased to a 42% lifetime BC risk using the £20 000 (US $27 037) per QALY WTP threshold. The identified lifetime BC risk thresholds for RRM to be cost-effective among women aged 35, 40, 45, 50, 55, and 60 years were 31%, 29%, 29%, 32%, 36%, and 42%, respectively, using the £30 000 (US $40 555) per QALY WTP threshold. Overall, undergoing RRM was deemed cost-effective for women aged 30 to 55 years with a lifetime BC risk of at least 35%, with more than 50% of simulations being cost-effective in probabilistic sensitivity analysis. Offering RRM for women with a lifetime BC risk of 35% or higher could potentially prevent approximately 6538 (95% CI, 4454-7041), or approximately 11% (95% CI, 8%-12%), of the 58 756 BC cases occurring annually in women in the UK. In the probabilistic sensitivity analysis, 20.71% to 59.96%, 44.04% to 81.29%, and 97.26% to 99.35% of simulations were cost-effective for women with 35%, 40%, and 50% lifetime BC-risk undergoing RRM at age 30 under the £20 000 to £30 000 per QALY WTP threshold, respectively. In this economic evaluation, undergoing RRM appears cost-effective for women aged 30 to 55 years with a lifetime BC risk of 35% or higher. These results could have significant clinical implications to expand access to RRM beyond BRCA1/BRCA2/PALB2 pathogenic variant carriers. Future studies evaluating the acceptability, uptake, and long-term outcomes of RRM among these women are warranted.

BMI and waist circumference (WC) are used to identify individuals with elevated obesity-related health risks. The current thresholds were derived largely in populations of European origin. This study determined optimal BMI and WC thresholds for the identification of cardiometabolic risk among white and African-American (AA) adults. The sample included 2096 white women, 1789 AA women, 1948 white men, and 643 AA men aged 18-64 years. Elevated cardiometabolic risk was defined as ≥2 risk factors (blood pressure ≥ 130/85 mm Hg; glucose ≥100 mg/dl; triglycerides ≥150 mg/dl; high-density lipoprotein-cholesterol <40 mg/dl (men) or <50 mg/dl (women)). Receiver Operating Characteristic (ROC) curves were used to identify optimal BMI and WC thresholds in each sex-by-ethnicity group. The optimal BMI thresholds were 30 kg/m2 in white women, 32.9 kg/m2 in AA women, 29.1 kg/m2 white men, and 30.4 kg/m2 in AA men, whereas optimal WC thresholds were 91.9 cm in white women, 96.8 cm in AA women, 99.4 in white men, and 99.1 cm in AA men. The sensitivities at the optimal thresholds ranged from 63.5 to 68.5% for BMI and 68.4 to 71.0% for WC and the specificities ranged from 64.2 to 68.8% for BMI and from 68.5 to 71.0% for WC, respectively. In general, the optimal BMI and WC thresholds approximated currently used thresholds in men and in white women. There are no apparent ethnic differences in men; however, in AA women the optimal BMI and WC values are ~3 kg/m2 and 5 cm higher than in white women.