Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. The long-term goal of our proposed project is to reduce the population burden of CRC by providing the information needed to address key policy questions and prioritize future research. To accomplish this goal we will use our population- based microsimulation models to: 1) Inform emerging issues in health policy across the CRC-control spectrum; 2) Guide CRC research priorities and study design using a value of information (VOI) framework; and 3) Engage stakeholders, train modelers, and promote model transparency to ensure high-quality evaluation of CRC control measures, now and in the future. Our team will fill critical gaps in knowledge, enabling decision makers to act. Important gaps in knowledge include the impact of failures in screening and treatment processes on CRC burden; the potential to safely reduce screening and surveillance intensity among some patients based on currently available tools for risk-stratification; the potential benefit of new targeted screening approaches based on patient-level information (i.e., precision medicine); and the importance of clinical management of diminutive polyps. The three participating modeling groups are well-positioned to carry out this work, bringing a wealth of experience, expertise, and insight to issues related to microsimulation modeling of CRC, and have a proven track record of collaborating and disseminating our work to health policy decision makers.
Despite large increases in screening in the past two decades, colorectal cancer remains the second leading cause of cancer death in the United States. Our research has shown that 60% of these deaths could be prevented by better use of available screening interventions. In this proposal, we use microsimulation modeling to help prioritize interventions and future research to further reduce the burden of colorectal cancer.
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