The purpose of this project is to further develop a population- based policy model that is specific for the prevention, detection, and treatment of colorectal cancer in the United States. The model will be a dynamic Monte Carlo simulation of the U.S. population that will include all of the modifiable and non-modifiable risk factors that have been found in epidemiological studies to be associated with the incidence of colorectal cancer: smoking history, body mass index, physical activity, red meat consumption, fruit and vegetable consumption, aspirin use, multivitamin use (as a proxy for folate intake), alcohol consumption, postmenopausal hormone use, and family history of colorectal cancer, as well as demographic variables (age, gender, race). Risk equations will be derived primarily from the Nurses' Health Study and the Health Professionals Follow-up Study; risk factor distributions over time in the U.S. population will be obtained primarily from the NHANES I, II, and III. The model will track the underlying progression and location of adenomatous polyps and undiagnosed cancer, thus enabling a screening test to detect and remove an adenomatous polyp, or to possibly detect a cancer at an earlier stage. Once a cancer is detected and staged (either by a screening test or by symptoms), all relevant colorectal cancer treatment strategies will be incorporated, allowing for the evaluation of current or hypothetical interventions. The model will be used to analyze the potential contributors to the observed cancer trends and to predict the potential impact on national trends of risk factor interventions, screening, and colorectal cancer treatment. Throughout this project, the research team will collaborate with the National Cancer Institute to incorporate national data sources and to focus research questions. The research team will also be involved with other modeling groups for purposes of calibration, validation, and the comparison of model results.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA088204-03
Application #
6522868
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
2002-09-01
Budget End
2003-08-31
Support Year
3
Fiscal Year
2002
Total Cost
$290,121
Indirect Cost
Name
Harvard University
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
City
Boston
State
MA
Country
United States
Zip Code
02115
Haug, Ulrike; Knudsen, Amy B; Lansdorp-Vogelaar, Iris et al. (2015) Development of new non-invasive tests for colorectal cancer screening: the relevance of information on adenoma detection. Int J Cancer 136:2864-74
Goede, Simon L; Kuntz, Karen M; van Ballegooijen, Marjolein et al. (2015) Cost-Savings to Medicare From Pre-Medicare Colorectal Cancer Screening. Med Care 53:630-8
Haug, Ulrike; Knudsen, Amy B; Kuntz, Karen M (2012) How should individuals with a false-positive fecal occult blood test for colorectal cancer be managed? A decision analysis. Int J Cancer 131:2094-102
Lansdorp-Vogelaar, Iris; Kuntz, Karen M; Knudsen, Amy B et al. (2012) Contribution of screening and survival differences to racial disparities in colorectal cancer rates. Cancer Epidemiol Biomarkers Prev 21:728-36
Knudsen, Amy B; Hur, Chin; Gazelle, G Scott et al. (2012) Rescreening of persons with a negative colonoscopy result: results from a microsimulation model. Ann Intern Med 157:611-20
Vanness, David J; Knudsen, Amy B; Lansdorp-Vogelaar, Iris et al. (2011) Comparative economic evaluation of data from the ACRIN National CT Colonography Trial with three cancer intervention and surveillance modeling network microsimulations. Radiology 261:487-98
Kuntz, Karen M; Lansdorp-Vogelaar, Iris; Rutter, Carolyn M et al. (2011) A systematic comparison of microsimulation models of colorectal cancer: the role of assumptions about adenoma progression. Med Decis Making 31:530-9
Lansdorp-Vogelaar, Iris; Knudsen, Amy B; Brenner, Hermann (2011) Cost-effectiveness of colorectal cancer screening. Epidemiol Rev 33:88-100
van Ballegooijen, Marjolein; Rutter, Carolyn M; Knudsen, Amy B et al. (2011) Clarifying differences in natural history between models of screening: the case of colorectal cancer. Med Decis Making 31:540-9
Berrington de González, Amy; Kim, Kwang Pyo; Knudsen, Amy B et al. (2011) Radiation-related cancer risks from CT colonography screening: a risk-benefit analysis. AJR Am J Roentgenol 196:816-23

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