Abstract 2317: Development and validation of a colorectal cancer prediction model: A nationwide cohort-based study

Abstract Background: Colorectal cancer (CRC) ranks as the third most prevalent cancer globally and is a major cause of cancer-related mortality. Early diagnosis is critical to increase survival rates. While CRC screening has shown significant benefit, adherence remains low, and there is a need for better tools to identify high-risk patients. Risk prediction models were demonstrated to identify such patients. Aim: To establish an individualized risk prediction model for CRC diagnosis based on Electronic Health Records (EHR). Methods: This is a retrospective cohort study utilizing EHR data of Clalit Health Services (CHS) members aged 50-74 that were eligible for CRC screening, from January 2013 to January 2019. The model was trained to predict CRC diagnosis within two years using approximately 20, 000 EHR features including socio-demographic information, laboratory results and medical history. Model performance, as a complementary screening method, was evaluated. Results: The study included 2679 subjects with CRC diagnosis and 1, 133, 713 subjects without CRC diagnosis. The model was trained on subjects from 2013-2017, and performance was validated on subjects from 2019 and a cohort of subjects that underwent fecal occult blood test (FOBT). Incidence values of CRC among subjects in the top 1% risk scores were higher than baseline (2. 3% vs. 0. 3%; lift 8. 38; P-value 0. 001). Characteristics of subjects by risk scores percentiles are presented in Table 1. Cumulative event probabilities increased with higher model scores, indicating a correlation between predicted and actual risk of CRC diagnosis. Model-based risk stratification among subjects with a positive FOBT, identified subjects with more than twice the risk for CRC compared to FOBT alone. Conclusions: We developed an individualized risk prediction model for CRC that can be utilized as a complementary decision support tool for healthcare providers to precisely identify patients at high risk for CRC and refer them to confirmatory testing. Citation Format: Samah Hayek. Development and validation of a colorectal cancer prediction model: A nationwide cohort-based study abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 2317.