This is the first resubmission of a BLR&D CDA-2 proposal to provide five years of salary support to Brian Sullivan, M.D. M.H.S., toward his goal of developing an independent VA research career. Dr. Sullivan is an Investigator at the Durham Cooperative Studies Epidemiology Center (CSPEC), Directory of Quality at the Durham VA Medical Center, and Assistant Professor at Duke University in the Department of Medicine. The long-term goal of this CDA is to provide Dr. Sullivan with the training and resources needed to lead a multi- disciplinary VA research program focused on colorectal cancer (CRC) prevention. There is considerable variability in individual risk of CRC that could impact age at initiation of CRC screening, screening modality choice, and frequency of follow-up. Yet, guidelines do not recognize this variability, performing too much colonoscopy screening and surveillance in low risk individuals and not providing enough or timely screening and surveillance in high-risk individuals. More precise risk stratification based on clinical and genetic factors offers a promising strategy to improve CRC prevention by targeting colonoscopy resources to individuals at increased risk for CRC, while reducing the costs and harms of invasive procedures in those at low risk who could undergo delayed or non-invasive screening. This CDA will leverage powerful VA resources, including linked clinical repositories and genomic biobanks, to enhance current CRC risk-assessment algorithms with individual-level information to develop cost-effective and “smarter” CRC risk prediction tools that can guide cancer prevention. Building on his prior work, Dr. Sullivan's short-term CDA goal is to create an accurate CRC risk prediction tool based on the clinical and genetic profiles of Veterans to improve CRC risk prediction and better target CRC screening resources. Specifically, he will establish a CRC risk cohort derived from natural language processing (NLP)-based phenotype algorithms to more accurately identify cases of CRC and advanced precancerous lesions in large VA administrative databases, then apply emerging statistical models for longitudinal cohorts that incorporates clinical information from prior screenings (if available) or other testing to allow informative estimates of CRC risk over time while taking competing risks of mortality into account (Aim 1). He will then link this database to the racially diverse Million Veteran Program (MVP) biorepository to test if additional CRC genomic discovery can bridge disparities and identify those at risk for CRC by creating a trans-ancestry polygenic risk score (Aim 2). Finally, he will augment genetic tools with known longitudinal CRC risk factors to create an accurate CRC risk prediction tool (Aim 3). This work will support future Merit applications for prospective validation and implementation studies of this tool. Dr. Sullivan has a team of expert mentors (including Drs. Elizabeth Hauser, Jason Dominitz, David Lieberma...