Every year, over 50,000 women in the United States are diagnosed with the non-lethal form of breast cancer known as ductal carcinoma in situ (DCIS). When a diagnosis of DCIS is confirmed on biopsy, most women are treated with partial mastectomy and breast irradiation or elect total mastectomy as a means to avoid radiation therapy. Newer approaches to treatment for DCIS have suggested that surgical excision and observation, with or without endocrine therapy, may be an alternative for small volume, low grade DCIS. However, as a general rule, the underlying biology of DCIS is just beginning to be considered in the context of treating DCIS. A substantial body of basic science regarding the underlying molecular alterations present in DCIS suggests there are two major pathways of progression constituting an indolent and aggressive form of DCIS. The goal of this proposal Is to translate the research data on the numerous molecular genetic abnormalities present In DCIS into a pathology classification algorithm based on a restricted set of molecular, immunohistochemical, or morphologic features that will reliably Identify low grade and high grade progression pathways in DCIS. This would promote conservative treatment strategies for a subset of women with favorable prognosis DCIS and reduce the potential unfavorable consequences of over treating indolent breast disease.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA163303-02
Application #
8555417
Study Section
Special Emphasis Panel (ZCA1-SRLB-R (O1))
Project Start
2011-09-23
Project End
2016-05-31
Budget Start
2012-09-01
Budget End
2013-05-31
Support Year
2
Fiscal Year
2012
Total Cost
$191,175
Indirect Cost
$66,739
Name
University of Vermont & St Agric College
Department
Type
DUNS #
066811191
City
Burlington
State
VT
Country
United States
Zip Code
05405
Munoz, Diego F; Plevritis, Sylvia K (2018) Estimating Breast Cancer Survival by Molecular Subtype in the Absence of Screening and Adjuvant Treatment. Med Decis Making 38:32S-43S
Buist, Diana S M; Abraham, Linn; Lee, Christoph I et al. (2018) Breast Biopsy Intensity and Findings Following Breast Cancer Screening in Women With and Without a Personal History of Breast Cancer. JAMA Intern Med 178:458-468
Sprague, Brian L; Vacek, Pamela M; Herschorn, Sally D et al. (2018) Time-varying risks of second events following a DCIS diagnosis in the population-based Vermont DCIS cohort. Breast Cancer Res Treat :
Plevritis, Sylvia K; Munoz, Diego; Kurian, Allison W et al. (2018) Association of Screening and Treatment With Breast Cancer Mortality by Molecular Subtype in US Women, 2000-2012. JAMA 319:154-164
Trentham-Dietz, Amy; Ergun, Mehmet Ali; Alagoz, Oguzhan et al. (2018) Comparative effectiveness of incorporating a hypothetical DCIS prognostic marker into breast cancer screening. Breast Cancer Res Treat 168:229-239
Conklin, Matthew W; Gangnon, Ronald E; Sprague, Brian L et al. (2018) Collagen Alignment as a Predictor of Recurrence after Ductal Carcinoma In Situ. Cancer Epidemiol Biomarkers Prev 27:138-145
Lee, Janie M; Abraham, Linn; Lam, Diana L et al. (2018) Cumulative Risk Distribution for Interval Invasive Second Breast Cancers After Negative Surveillance Mammography. J Clin Oncol 36:2070-2077
van den Broek, Jeroen J; van Ravesteyn, Nicolien T; Mandelblatt, Jeanne S et al. (2018) Comparing CISNET Breast Cancer Models Using the Maximum Clinical Incidence Reduction Methodology. Med Decis Making 38:112S-125S
Mandelblatt, Jeanne S; Near, Aimee M; Miglioretti, Diana L et al. (2018) Common Model Inputs Used in CISNET Collaborative Breast Cancer Modeling. Med Decis Making 38:9S-23S
McCarthy, Anne Marie; Barlow, William E; Conant, Emily F et al. (2018) Breast Cancer With a Poor Prognosis Diagnosed After Screening Mammography With Negative Results. JAMA Oncol 4:998-1001

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