Tailored health care interventions based on information specific to an individual, including family history and genomics, are expected to transform clinical practice in the near future. Personalized medicine targeted at preventing diseases holds great promise because it can reduce the need for high-cost treatments and improve the overall health of the nation. Therefore, there is an imminent need to assess the projected impact of personalized medicine on both health outcomes and cost. We are proposing to develop a mathematical model for identifying the potential impacts of these preventive tests and to assess the threshold sensitivity, specificity, and cost under which these tests are likely to be adopted, which will be extremely beneficial in moving this field forward toward greater clinical application. The movement toward personalized medicine, which places greater importance on personal-level decision making, requires next-generation modeling using micro simulation techniques. Therefore, we are proposing to study the impact of personalized medicine on the cost-effectiveness of prevention using an agent-based model (ABM) to simulate individual behaviors and interactions and to assess their collective impacts at the population level. We will build a prototype model for colorectal cancer (CRC) prevention and screening to demonstrate the utility and feasibility of this modeling approach.
The specific aims of this research are as follows:
Specific Aim 1. Develop a framework for performing micro simulation modeling to assess the impact of personalized medicine and genomics on the costs and benefits of prevention.
Specific Aim 2. Create a prototype model for CRC prevention to demonstrate the feasibility of developing an ABM to assess individual-level differences.
Specific Aim 3. Identify the thresholds under which personalized approaches, including genetic testing, for CRC prevention could potentially be cost-saving or cost-effective. The overall goal of this research is to provide a framework that can foster the use of ABMs to study the impact of personalized medicine on the cost-effectiveness of prevention for a wide range of diseases, including other cancers, diabetes, heart disease, and obesity.

Public Health Relevance

Personalized medicine targeted at preventing diseases holds great promise because it can reduce the need for high-cost treatments and improve the overall health of the nation. Developing a mathematical model to identify the potential impacts of these preventive tests and assessing the threshold sensitivity, specificity, and cost under which these tests are likely to be adopted will be extremely beneficial in moving this field forward toward greater clinical application. We will build a prototype model for colorectal cancer prevention and screening to demonstrate the utility and feasibility of this modeling approach.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21CA165093-02
Application #
8337804
Study Section
Special Emphasis Panel (ZRG1-HDM-C (50))
Program Officer
Breen, Nancy
Project Start
2011-09-23
Project End
2014-08-31
Budget Start
2012-09-07
Budget End
2014-08-31
Support Year
2
Fiscal Year
2012
Total Cost
$133,658
Indirect Cost
$58,658
Name
Research Triangle Institute
Department
Type
DUNS #
004868105
City
Research Triangle
State
NC
Country
United States
Zip Code
27709
Subramanian, Sujha; Chen, Amy (2013) Treatment patterns and survival among low-income medicaid patients with head and neck cancer. JAMA Otolaryngol Head Neck Surg 139:489-95