The goals of this NCI cooperative research program (CISNET) are to explain the US breast cancer incidence and mortality trends, and to predict changes in the trends with new interventions. We will collaboratively with CISNET investigators toward developing validated computer-based simulation analyses that will attain these goals. In addition, we will contribute to CISNET novel research ideas and validated methods to quantify the impact of biological factors on breast cancer trends.
The specific aims of this research effort will be: (1) to develop a stochastic model of the natural history of breast cancer that describes the growth rate of the primary tumor, the size of the primary tumor when it sheds its first metastatic cell, and the growth rate of metastases; (2) to simulate the progression of breast cancer in the US population using a natural history model of breast cancer; (3) to explain and predict US breast cancer trends with validated computer simulation tools that incorporate a natural history model of the disease. Awareness of biological factors on the breast cancer trends may provide new insights for more effectively targeting future breast cancer control programs.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01CA088248-01
Application #
6198077
Study Section
Special Emphasis Panel (ZCA1-SRRB-3 (M1))
Program Officer
Feuer, Eric J
Project Start
2000-09-01
Project End
2004-08-31
Budget Start
2000-09-01
Budget End
2001-08-31
Support Year
1
Fiscal Year
2000
Total Cost
$173,371
Indirect Cost
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
800771545
City
Stanford
State
CA
Country
United States
Zip Code
94305
Alagoz, Oguzhan; Berry, Donald A; de Koning, Harry J et al. (2018) Introduction to the Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Models. Med Decis Making 38:3S-8S
Gallaher, Jill; Babu, Aravind; Plevritis, Sylvia et al. (2014) Bridging population and tissue scale tumor dynamics: a new paradigm for understanding differences in tumor growth and metastatic disease. Cancer Res 74:426-435
Schackmann, Elizabeth A; Munoz, Diego F; Mills, Meredith A et al. (2013) Feasibility evaluation of an online tool to guide decisions for BRCA1/2 mutation carriers. Fam Cancer 12:65-73
Lin, Ray S; Plevritis, Sylvia K (2012) Comparing the benefits of screening for breast cancer and lung cancer using a novel natural history model. Cancer Causes Control 23:175-85
Sigal, Bronislava M; Munoz, Diego F; Kurian, Allison W et al. (2012) A simulation model to predict the impact of prophylactic surgery and screening on the life expectancy of BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev 21:1066-77
Kurian, Allison W; Munoz, Diego F; Rust, Peter et al. (2012) Online tool to guide decisions for BRCA1/2 mutation carriers. J Clin Oncol 30:497-506
Bailey, Stephanie L; Sigal, Bronislava M; Plevritis, Sylvia K (2010) A simulation model investigating the impact of tumor volume doubling time and mammographic tumor detectability on screening outcomes in women aged 40-49 years. J Natl Cancer Inst 102:1263-71
Kurian, Allison W; Sigal, Bronislava M; Plevritis, Sylvia K (2010) Survival analysis of cancer risk reduction strategies for BRCA1/2 mutation carriers. J Clin Oncol 28:222-31
Mandelblatt, Jeanne S; Cronin, Kathleen A; Bailey, Stephanie et al. (2009) Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms. Ann Intern Med 151:738-47
Plevritis, Sylvia K; Kurian, Allison W; Sigal, Bronislava M et al. (2006) Cost-effectiveness of screening BRCA1/2 mutation carriers with breast magnetic resonance imaging. JAMA 295:2374-84

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