J Cancer 2022; 13(10):3103-3112. doi:10.7150/jca.74772 This issue Cite
Research Paper
Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
*These authors contributed equally to this work.
Purpose: To establish and validate a model to determine the occurrence risk of colorectal ademomatous polyps.
Methods: A large cohort of 3576 eligible participants who were treated in the Department of Gastroenterology, the First Affiliated Hospital of Nanjing Medical University from June 2019 to December 2021, were enrolled in our study and divided into discovery and validation cohorts at a ratio of 7:3. LASSO regression method was applied for data dimensionality reduction and feature selection. The nomogram for the occurrence risk of colorectal ademomatous polyps was constructed based on multivariate logistic regression. The predictive performance of the model was evaluated regarding its discrimination, calibration, and clinical applicability.
Results: A total of 10 high-risk factors were independent predictors of the colorectal ademomatous polyps occurrence and incorporated into the nomogram, including older age, male, hyperlipidemia, smoking, high consumption of red meat, high consumption of salt, high consumption of dietary fiber, Helicobacter pylori infection, non-alcoholic fatty liver disease and chronic diarrhea. The model showed favorable discrimination values, with the area under the curve of the discovery and validation cohorts 0.775 (95% confidence interval (CI), 0.755-0.794) and 0.776 (95% CI, 0.744-0.807) respectively. The model was also well-calibrated, with Hosmer-Lemeshow test P = 0.370. In addition, the decision curve analysis revealed that the model had a higher net profit compared with either the screen-all scheme or the screen-none scheme.
Conclusion: In this prospective study, we established and validated a prediction model that incorporated a list of high-risk features related to colorectal ademomatous polyps occurrence, showing favorable discrimination and calibration values.
Keywords: Colorectal ademomatous polyps, Colorectal cancer, Prediction model, Occurrence risk