Ghosh, Karthik

Key Clinical MessageThe differential diagnosis of a large breast mass in a post‐menopausal woman can include both benign and malignant etiologies. Although rare, diagnosis of giant intraductal papilloma must be considered in the differential. Furthermore, although benign, papillomas presenting as a large breast mass affecting the skin require extensive breast surgical treatment.

Abstract Atypical hyperplasia is a high-risk premalignant lesion of the breast, but its biology is poorly understood. Many believe that atypical ductal hyperplasia (ADH) is a direct precursor for low-grade ductal breast cancer, whereas atypical lobular hyperplasia (ALH) serves as a risk indicator. These assumptions underlie current clinical recommendations. We tested these assumptions by studying the characteristics of the breast cancers that develop in women with ADH or ALH. Using the Mayo Benign Breast Disease Cohort, we identified all women with ADH or ALH from 1967 to 2001 and followed them for later breast cancers, characterizing side of breast cancer versus side of atypia; time to breast cancer; type, histology, and grade of breast cancer, looking for patterns consistent with precursors versus risk indicators. A total of 698 women with atypical hyperplasia were followed a mean of 12.5 years; 143 developed breast cancer. For both ADH and ALH, there is a 2:1 ratio of ipsilateral to contralateral breast cancer. The ipsilateral predominance is marked in the first 5 years, consistent with a precursor phenotype for both ADH and ALH. For both, there is a predominance of invasive ductal cancers with 69% of moderate or high grade. Twenty-five percent are node positive. Both ADH and ALH portend risk for ductal carcinoma in situ and invasive breast cancers, predominantly ductal, with two thirds moderate or high grade. The ipsilateral breast is at especially high risk for breast cancer in the first 5 years after atypia, with risk remaining elevated in both breasts long term. ADH and ALH behave similarly in terms of later breast cancer endpoints. Cancer Prev Res; 7(2); 211–7. ©2014 AACR.

Background: Current recommendations for surgical management of early-stage breast cancer include breast-conserving surgery with postoperative irradiation. However, studies show that mastectomy is still being used by women with early-stage breast cancer. Methods: Review of the medical literature published between 2000 and 2010 to determine the factors associated with the decision of patients for surgical treatment in early-stage breast cancer. Results: The following patient characteristics affect the surgical decision-making process in early-stage breast cancer: age, socioeconomic factors, geographic area in which the patient lives, proximity to a radiation therapy center, testing for BRCA gene, breast imaging, and decision aids. Conclusions: Of increasing importance in the decision making about treatment of women with early-stage breast cancer are the woman's perception of having a surgical choice and the influence of that choice on postoperative quality of life.

Abstract INTRODUCTION: Mammographic breast density is a strong risk factor for breast cancer (BC). We established the Mayo Mammography Health Study (MMHS) cohort study at the Mayo Clinic in Rochester, Minnesota (MN) to examine the association of breast density with BC. We evaluated the influence of the image acquisition technique on the density and BC association. METHODS: From October 2003 to September 2006, all women scheduled for screening mammography at the Mayo Clinic were invited to participate. Eligible women were residents of MN, Iowa (IA) or Wisconsin (WI); age 35+; and had no personal history of BC. A risk factor questionnaire, consent form and permission to link to tumor registries were obtained. Incident BC was identified through 2009 by linkage to the Mayo and state cancer registries. A case-cohort of all incident BCs and 2300 randomly selected women (the subcohort) were used to examine the association of breast density and BC using digitized film mammograms at the time of enrollment while controlling for the influence of the acquisition parameters (peak kilovoltage, milliampere-second, and compressed breast thickness). Two density measures were considered: a quantitative percent density (PD) measure estimated using the computer-assisted thresholding program, Cumulus (University of Toronto), and the 4-category clinical BI-RADS measure. Proportional hazards regression was used to calculate hazards ratios (HR) and 95% confidence intervals (CI) for BC associated with quartiles of PD (0-6.2%,6.3-14.9%, 15.0-25.7% and 25.8%+) and BI-RADS categories 1-4 (almost entirely fatty to extremely dense). All models included age, postmenopausal hormone use (PMH), BMI, and menopausal status. The influence of acquisition parameters was evaluated by examining models with and without their inclusion. RESULTS: A total of 20,982 (50%) women participated in MMHS; 1058 (5%) with a prior history of BC were excluded, for a total cohort of 19,924. Compared to nonresponders, responders were younger (57.5 vs. 58.4 yrs), more likely to have ever used PMH (45% vs. 33%), and more likely to have a BC family history (19% vs 16%). The case-cohort consisted of 317 incident cases and 2300 women in the subcohort. Women were excluded from the current analysis if PD could not be estimated or if acquisition parameters were not available, leaving 249 cases and 1937 in the subcohort. As expected, PD was associated with BC [HR (95% CI): 1.0 (REF), 2.1 (1.4-3.1), 3.0 (2.0-4.5), and 4.6 (3.0-7.0) for quartiles; p-trend<0.001]. Controlling for acquisition parameters attenuated the association [HR (95% CI): 1.0 (REF), 2.3 (1.5-3.4), 2.4 (1.6-3.7), and 3.0 (1.8-5.0) for quartiles; p-trend<0.001]. Results for BI-RADS density were similar to those for PD. CONCLUSION: This study confirms that breast density is a significant risk factor for BC and demonstrates that the acquisition technique confounds the density and BC risk association. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3716. doi:10.1158/1538-7445.AM2011-3716

Abstract B39 Background The breast glandular epithelium is composed of lobules that undergo age-related involution that increases as women age and has been associated with lowered breast cancer risk. Mammographic density (MD) is an established risk factor for breast cancer that has been shown to decrease with age. This study examined the association of age-related lobular involution with mammographic breast density. Materials and Methods The study sample was selected from approximately 20,000 healthy women who were enrolled in a screening cohort at the Mayo Clinic (Mayo Mammography Health Study) from 2003 to 2006 and had a benign breast biopsy (BBD) within 2 years of the enrollment mammogram. A quantitative measure of mammographic density, percent density (PD) was estimated on the enrollment mammogram, in addition to its components dense and nondense area (NDA). All biopsies were reviewed by a breast pathologist for the type of benign breast disease (BBD) as well as lobular involution status. Involution was defined as the proportion of terminal ductal lobular units (TDLUs) in the background tissue on biopsy that showed at least 50% decrease in size and number of acini from normal lobules and was subjectively assessed as: No- 0% involution, Partial- 1 to 74%, or Complete- >75% involution. Mean density was estimated for the 3 categories of involution using generalized linear models and square root transformation. Confounders were assessed including age, parity, body mass index (BMI), type of BBD, menopausal status, age at first birth and family history Results A total of 317 women from the MMHS had BBD within 2 years of enrollment. Mean age at BBD diagnosis in this sample was 55 years. Age- and BMI- adjusted analyses suggested an inverse association of involution and percent density with adjusted mean PD values of 23.3 (95%CI [17.2, 30.3]) for no involution, 21.9 (95%CI [20.0, 23.9]) for partial involution, and 17.8 (95% CI [14.7, 21.3]) for complete involution (p for trend 0.05). This trend was driven primarily by the positive association of involution with nondense area with adjusted mean NDA values of 103.1cm2 (95% CI [86.1, 121.7]) for no involution, 104.9 cm2 (95% CI [99.4, 110.7]) for partial involution, and 126.2 cm2 (95% CI [115.0, 137.9]) for complete involution (p for trend 0.004). Discussion Our findings suggest that MD is inversely associated with involution of breast tissues, providing a plausible mechanism through which MD influences breast cancer risk. Citation Information: Cancer Prev Res 2008;1(7 Suppl):B39.

Diabetic mastopathy is an uncommon, benign disease of the breast that can occur in women with diabetes and clinically mimic breast cancer. We describe a patient with long-standing type 1 diabetes who presented with a palpable breast mass with negative imaging findings on mammography, ultrasonography, and breast MRI. Surgical biopsy and histopathology confirmed diabetic mastopathy. We use this case to highlight the recognition, radiographic features, pathology, and management of this benign breast condition and emphasize that, in diabetic patients, the differential diagnosis of a new breast mass should include diabetic mastopathy.

Abstract Introduction: Mammographic breast density is one of the strongest risk factors for breast cancer and appears to be modifiable. However, whether longitudinal changes in density are associated with breast cancer risk is unknown. We hypothesize that decreases in breast density are associated with reduced breast cancer risk. Methods: The Mayo Mammography Health Study cohort enrolled 19,924 women having a screening mammogram (mgm) at the Mayo Clinic, Rochester, between 2003 and 2006. Participants were 35 years and older, had no prior breast cancer and lived in the tri-state area (MN, IA and WI). Risk factor data were collected through self-administered questionnaire and clinic databases. Incident breast cancers were identified through tumor registries (Mayo Clinic, MN, IA, WI). The BI-RADS, 4-category clinical density measure (fatty, scattered density, heterogeneous density and extreme density) was available on all mgms performed after 1996. A case-cohort design consisting of incident cases (n=241) and a random selection of the cohort (n=2300, 28 developed cancer) was used to examine the association between change in BI-RADS density and breast cancer. BI-RADS densities measured from the earliest available, and enrollment mgms (average 6 years apart) were used to assess density change. Proportional hazards regression was performed to estimate the hazard ratio (HR) associated with a change in one or more BI-RADS density categories over time, relative to staying within the same category. Age was used as the time scale, and the subcohort was weighted by the inverse of the sampling proportion. Analyses were adjusted for age, years between mgms, BI-RADS density at earliest mgm, and changes in BMI, postmenopausal hormone use, and menopausal status. Results: Longitudinal analyses were conducted on the 219 cases and 1900 non-cases in the subcohort with at least one mgm available prior to enrollment mgm. Compared to the subcohort, cases were older (56.8 vs. 52.9 years), more likely postmenopausal (73.4% vs. 61.6%), had higher BMI (29.0 vs 28.1) and were more frequently screened (8.0 vs. 6.9 pre-enrollment mgms). As expected, cases were more likely to have extreme density (BI-RADS=4) at earliest mgm than non-cases (16.2% vs 14.3%). Cases were less likely than non-cases to experience a reduction of one density category or more (37.0% vs 38.6%) following earliest mgm. Adjusting for potential confounders, women who decreased one BI-RADS category or more over an average 6 years were at reduced risk of breast cancer (HR=0.72, 95%CI: 0.50-0.99) compared to those whose density was unchanged. However, women who increased one or more BI-RADS categories had suggestion of increased risk (HR=1.52, 95%CI: 0.97-2.4). Conclusion: Women with a decrease in BI-RADS density category over 6 years may have decreased breast cancer risk relative to women whose breast density category remains stable. Two measures of breast density may inform women's risk beyond a measure at one point in time. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4828.

Purpose Mammographic density and lobular involution are both significant risk factors for breast cancer, but whether these reflect the same biology is unknown. We examined the involution and density association in a large benign breast disease (BBD) cohort. Patients and Methods Women in the Mayo Clinic BBD cohort who had a mammogram within 6 months of BBD diagnosis were eligible. The proportion of normal lobules that were involuted was categorized by an expert pathologist as no (0%), partial (1% to 74%), or complete involution (≥ 75%). Mammographic density was estimated as the four-category parenchymal pattern. Statistical analyses adjusted for potential confounders and evaluated modification by parity and age. We corroborated findings in a sample of women with BBD from the Mayo Mammography Health Study (MMHS) with quantitative percent density (PD) and absolute dense and nondense area estimates. Results Women in the Mayo BBD cohort (n = 2,667) with no (odds ratio, 1.7; 95% CI, 1.2 to 2.3) or partial (odds ratio, 1.3; 95% CI, 1.0 to 1.6) involution had greater odds of high density (DY pattern) than those with complete involution (P trend < .01). There was no evidence for effect modification by age or parity. Among 317 women with BBD in the MMHS study, there was an inverse association between involution and PD (mean PD, 22.4%, 21.6%, 17.2%, for no, partial, and complete, respectively; P trend = .04) and a strong positive association of involution with nondense area (P trend < .01). No association was seen between involution and dense area (P trend = .56). Conclusion We present evidence of an inverse association between involution and mammographic density.