Risk factors for breast cancer after the diagnosis of benign breast disease include the histologic classification of a benign breast lesion and a family history of breast cancer.
This selection from the NCCN Guidelines for Merkel Cell Carcinoma (MCC) focuses on areas impacted by recently emerging data, including sections describing MCC risk factors, diagnosis, workup, follow-up, and management of advanced disease with radiation and systemic therapy. Included in these sections are discussion of the new recommendations for use of Merkel cell polyomavirus as a biomarker and new recommendations for use of checkpoint immunotherapies to treat metastatic or unresectable disease. The next update of the complete version of the NCCN Guidelines for MCC will include more detailed information about elements of pathology and addresses additional aspects of management of MCC, including surgical management of the primary tumor and draining nodal basin, radiation therapy as primary treatment, and management of recurrence.
In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. IntroductionVariation in the radiographic appearance of the breast reflects differences in tissue composition [1]: darker regions indicate fat tissue and lighter regions represent dense tissue, primarily fibroglandular tissue consisting of the functional elements or parenchyma, and supporting elements or stroma [2]. The proportion of the lighter or dense regions on the mammogram, characterized as mammographic density (MD), has consistently been one of the strongest risk factors for breast cancer, with risk estimates that are three-to five-fold greater for women in the highest quartile of density than for women of similar age in the lowest quartile [3]. As increased MD is common in the population, with 26% to 32% of women in the general population having densities of 50% or greater (Table 1), 16% to 32% of breast cancers may be attributed to this trait [4,5], with an even larger estimated proportion among premenopausal women [6].The magnitude and consistency of the MD and breast cancer association place its importance as a breast cancer risk factor alongside age, the presence of atypia on a breast biopsy, or carrying a highly penetrant breast cancer susceptibility gene (for example, BRCA1 and BRCA2) [7], the latter two which are rare in the population and responsible for only a small proportion of breast cancer. However, until recently, MD has not been used in clinical risk prediction models or clinical decision making. The purpose of this review is to summarize the evidence and strength of MD as a risk factor, review the studies that have evaluated MD in risk prediction, and discuss the implications of incorporating this trait into clinical practice for improving breast cancer risk assessment. Part I. Mammographic density as a risk factor for breast cancerThe association between MD and breast cancer has been investigated in more than 50 studies over the last three decades. These studies have varied in their approaches to the measurement of MD ...
Among women with atypical hyperplasia, multiple foci of atypia and the presence of histologic calcifications may indicate "very high risk" status (> 50% risk at 20 years). A positive family history does not further increase risk in women with atypia.
Mammographic breast density is a strong risk factor for breast cancer but whether breast density is a general marker of susceptibility or is specific to the location of the eventual cancer is unknown. A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Mammograms on average 7 years before breast cancer were digitized, and quantitative measures of percentage density and dense area from each side and view were estimated. A regional density estimate accounting for overall percentage density was calculated from both mammogram views. Location of breast cancer and potential confounders were abstracted from medical records. Conditional logistic regression was used to estimate associations, and C-statistics were used to evaluate the strength of risk prediction. There were increasing trends in breast cancer risk with increasing quartiles of percentage density and dense area, irrespective of the side of the breast with cancer (P trends < 0.001). Percentage density from the ipsilateral side [craniocaudal (CC): odds ratios (ORs), 1.0 (ref), 1.7, 3
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 (BC) while 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 (BCs) that develop in women with ADH or ALH. Using the Mayo Benign Breast Disease Cohort, we identified all women with ADH or ALH from 1967–2001 and followed them for later BCs, characterizing side of BC vs side of atypia; time to BC; type, histology and grade of BC, looking for patterns consistent with precursors vs risk indicators. 698 women with atypical hyperplasia were followed a mean of 12.5 years; 143 developed BC. For both ADH and ALH, there is a 2:1 ratio of ipsilateral to contralateral BCs. The ipsilateral predominance is marked in the first five 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. 25% are node positive. Both ADH and ALH portend risk for DCIS and invasive BCs, predominantly ductal, with two thirds moderate or high-grade. The ipsilateral breast is at especially high risk for BC in the first five years after atypia, with risk remaining elevated in both breasts long-term. ADH and ALH behave similarly in terms of later BC endpoints.
Background: Mammographic density is a strong risk factor for breast cancer. However, whether changes in mammographic density are associated with risk remains unclear. Materials and Methods: A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Controls were matched on age, exam date, residence, menopause, interval between, and number of mammograms. All serial craniocaudal mammograms 10 years before ascertainment were digitized, and quantitative measures of percent density (PD) were estimated using a thresholding method. Data on potential confounders were abstracted from medical records. Logistic regression models with generalized estimating equations were used to evaluate the interactions among PD at earliest mammogram, time from earliest to each serial mammogram, and absolute change in PD between the earliest and subsequent mammograms. Analyses were done separately for PD measures from the ipsilateral and contralateral breast and also by use of hormone therapy (HT). Results: Subjects had an average of five mammograms available, were primarily postmenopausal (83%), and
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