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Grant Details

Grant Number: 5U01CA088204-09 Interpret this number
Primary Investigator: Kuntz, Karen
Organization: University Of Minnesota
Project Title: A Population Based Policy Model for Colorectal Cancer
Fiscal Year: 2009


Abstract

In the first CISNET project we developed a population-based Monte Carlo simulation model that evaluates national trends in the incidence and mortality of colorectal cancer (CRC). The HSPH-CISNET Model incorporates age-, sex-, and race-specific trends in CRC risk factors, screening, and treatment, as well as the effects of risk factors and screening on the underlying natural history of colorectal disease and the effectiveness of treatment for patients with diagnosed CRC. The Model currently simulates the US population aged 25 years and older from 1970 to 2020. We have used the Model to examine the relative contribution of changes in risk factors, screening, and treatment to the overall population trends in CRC incidence and mortality. The purpose of this project is to use the HSPH-CISNET Model to evaluate the population impact of existing cancer control strategies, as well as the impact of strategies on the horizon. Of particular importance is to incorporate the associations between risk factors and screening trends, and to determine the potential impact of disparities in CRC risk and mortality at a population level. Other aims will focus on evaluating the population-level impact of specific risk factor trends, screening modalities, and treatment advancements. To validate our modeling assumptions, we will use our model structure to simulate the population of Norway, a country that does not have a CRC screening program, in an attempt to re-create their incidence and mortality statistics. We will continue to collaborate with other modeling groups, as well as with the new CRC Coordinating Center and the NCI to focus on questions that apply across all modeling groups. In addition, we propose a concrete plan for making our model more accessible to outside collaborators. This plan involves posting the model structure on a public website, sharing code with established outside investigators, and providing the necessary model support.



Publications

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