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      Mammographic density and survival in interval breast cancers

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          Abstract

          Introduction

          Mammographic density (MD) is the strongest risk factor for breast cancer. It is also strongly associated with interval cancers (ICs) due to decreased screening sensitivity and possibly by also giving rise to more aggressive tumors. With this information as background, we compared survival in interval and screen-detected cancers, taking MD into consideration.

          Methods

          The patients were postmenopausal women ages 50 to 74 years who were diagnosed with breast cancer in Sweden between 1993 and 1995. A total of 1,115 women with screen-detected cancers and 285 with ICs had available mammograms. Cox proportional hazards models were used to compare breast cancer-specific survival between interval and screen-detected cancers stratified on MD.

          Results

          Hazard rates for breast cancer-specific survival were approximately three times higher in ICs than in screen-detected cancers, independent of MD. After adjustment for tumor size, a proxy for time to diagnosis, ICs in nondense breasts still had a statistically significantly increased hazard rate compared to screen-detected cancers in nondense breasts (5-yr survival hazard ratio (HR) 2.43, P = 0.001). In dense breasts, however, there was no longer evidence of a difference in survival between ICs and screen-detected cancers (5-yr survival HR 1.41, P = 0.486).

          Conclusions

          In nondense breasts, ICs seem to be truly more aggressive than screen-detected cancers. In dense breasts, the poorer prognosis of ICs compared to that of screen-detected cancers may be attributable at least partially to later detection. However, to the best of our knowledge, this study is the first to investigate these relationships, and further studies are warranted to confirm our results.

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          Most cited references27

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          Stromal gene expression predicts clinical outcome in breast cancer.

          Although it is increasingly evident that cancer is influenced by signals emanating from tumor stroma, little is known regarding how changes in stromal gene expression affect epithelial tumor progression. We used laser capture microdissection to compare gene expression profiles of tumor stroma from 53 primary breast tumors and derived signatures strongly associated with clinical outcome. We present a new stroma-derived prognostic predictor (SDPP) that stratifies disease outcome independently of standard clinical prognostic factors and published expression-based predictors. The SDPP predicts outcome in several published whole tumor-derived expression data sets, identifies poor-outcome individuals from multiple clinical subtypes, including lymph node-negative tumors, and shows increased accuracy with respect to previously published predictors, especially for HER2-positive tumors. Prognostic power increases substantially when the predictor is combined with existing outcome predictors. Genes represented in the SDPP reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses, highlighting the importance of stromal biology in tumor progression.
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            Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers.

            Screening mammography is the best method to reduce mortality from breast cancer, yet some breast cancers cannot be detected by mammography. Cancers diagnosed after a negative mammogram are known as interval cancers. This study investigated whether mammographic breast density is related to the risk of interval cancer. Subjects were selected from women participating in mammographic screening from 1988 through 1993 in a large health maintenance organization based in Seattle, WA. Women were eligible for the study if they had been diagnosed with a first primary invasive breast cancer within 24 months of a screening mammogram and before a subsequent one. Interval cancer case subjects (n = 149) were women whose breast cancer occurred after a negative or benign mammographic assessment. Screen-detected control subjects (n = 388) were diagnosed after a positive screening mammogram. One radiologist, who was blinded to cancer status, assessed breast density by use of the American College of Radiology Breast Imaging Reporting and Data System. Mammographic sensitivity (i.e., the ability of mammography to detect a cancer) was 80% among women with predominantly fatty breasts but just 30% in women with extremely dense breasts. The odds ratio (OR) for interval cancer among women with extremely dense breasts was 6.14 (95% confidence interval [CI] = 1.95-19.4), compared with women with extremely fatty breasts, after adjustment for age at index mammogram, menopausal status, use of hormone replacement therapy, and body mass index. When only those interval cancer cases confirmed by retrospective review of index mammograms were considered, the OR increased to 9.47 (95% CI = 2.78-32.3). Mammographic breast density appears to be a major risk factor for interval cancer.
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              Mammographic density and breast cancer risk: current understanding and future prospects

              Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making.
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                Author and article information

                Contributors
                Journal
                Breast Cancer Res
                Breast Cancer Res
                Breast Cancer Research : BCR
                BioMed Central
                1465-5411
                1465-542X
                2013
                20 June 2013
                : 15
                : 3
                : R48
                Affiliations
                [1 ]Institution of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, S-171 77 Stockholm, Sweden
                [2 ]Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Mörbygårdsvägen 5, S-182 88 Stockholm, Sweden
                [3 ]Cancer Screening Unit, Oncologic Center, Norrbacka S3:00, Karolinska University Hospital, Solna, S-171 76 Stockholm, Sweden
                Article
                bcr3440
                10.1186/bcr3440
                4053151
                23786804
                eb580e61-f43f-46e6-bc53-2affa33a7fe4
                Copyright © 2013 Eriksson et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 March 2013
                : 20 June 2013
                Categories
                Research Article

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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