Grant Number:	5R01CA243449-04 Interpret this number
Primary Investigator:	Butterly, Lynn
Organization:	Dartmouth-Hitchcock Clinic
Project Title:	Optimizing Colorectal Cancer Prevention: a Multi-Disciplinary, Population-Based Investigation of Serrated Polyps Using Risk Prediction and Modeling
Fiscal Year:	2023

Project Summary/Abstract Colorectal cancer (CRC), the second most common cause of cancer deaths in the US, can be prevented through colonoscopy, during which potentially pre-cancerous polyps are removed from the colon. Serrated polyps may precede up to 30% of CRC, but unlike adenomatous polyps (their more common counterparts), there is limited data about their outcomes and natural history. Current clinical guidelines highlight that there is a critical lack of evidence available on future risks in patients with serrated polyps. To address this knowledge gap, this project proposes to combine the comprehensive data on colonoscopy patients, procedures, and pathology of the New Hampshire Colonoscopy Registry (NHCR), which has been collecting data from endoscopy sites across NH since 2004, with the statistical and risk prediction modeling expertise of the Geisel School of Medicine at Dartmouth College and the internationally recognized micro-simulation modelers of the Cancer Intervention and Surveillance Network (CISNET). The development and application of microsimulation models to characterize how digestive diseases progress is a key need for improving public health. In Aim 1.1, NHCR data, including key information on polyp subtype, size and location in the colon as well as the interval between index and subsequent colonoscopy, will be used to develop a risk-prediction model that can generate accurate personalized estimates of future risk in patients with serrated polyps. In Aim 1.2, NHCR data on patient risk factors and characteristics will be added to this model, to further refine the personalized estimates of future risk. In Aim 2.1, these risk estimates and additional NHCR data from patients with serrated lesions will be used by members of the CISNET Colorectal Group to inform and expand existing colorectal cancer micro-simulation models (SimCRC and MISCAN), and, in Aim 2.2, adding data from the literature, to validate these models. Aim 3.1 will use these expanded micro-simulation models to assess the clinical and cost effectiveness of recommended follow-up intervals for colonoscopy surveillance in patients with serrated polyps, stratified by specific polyp characteristics. Aim 3.2 will use the models to assess the effectiveness of recommended follow-up intervals for surveillance in patients with serrated polyps stratified by both polyp and patient characteristics. By linking the data of the NHCR with the biostatistical tools of risk-prediction and micro-simulation modelling, this study will significantly advance the scientific evidence-base and transform the landscape of serrated polyp management, helping colonoscopy achieve its tremendous potential for reducing CRC incidence and mortality.





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