A large cohort of eligible participants were included in the analysis, and classified into derivation and validation cohorts at a ratio of 7:3. Demographic and clinicopathological characteristics of participants were utilized to develop a prediction model for colorectal polyps. In the derivation cohort, the LASSO regression method was applied to filter variables and select the most useful high-risk factors. Multivariate logistic regression analysis was used to identify potential predictors and then a prediction model was established. The predictive performance of the model was evaluated with respect to its discrimination, calibration and clinical usefulness.
This prospective case-control study aimed to analyze and summarize the high-risk factors and susceptible genes of patients with colorectal polyps. According to these high-risk factors, the investigators developed and validated a prediction model for colorectal polyps to identify high-risk individuals, in order to provide clinical basis for the etiology research and the establishment of effective preventive measures.