Noninvasive predictive models based on lifestyle analysis and risk factors for early-onset colorectal cancer

Colorectal cancer (CRC) incidence has increased among patients aged <50 years. Exploring high-risk factors and screening high-risk populations may help lower early-onset CRC (EO-CRC) incidence. We developed noninvasive predictive models for EO-CRC and investigated its risk factors. This retrospec...

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Published in:Journal of gastroenterology and hepatology Vol. 38; no. 10; pp. 1768 - 1777
Main Authors: Deng, Jia-Wen, Zhou, Yi-Lu, Dai, Wei-Xing, Chen, Hui-Min, Zhou, Cheng-Bei, Zhu, Chun-Qi, Ma, Xin-Yue, Pan, Si-Yuan, Cui, Yun, Xu, Jia, Zhao, En-Hao, Wang, Ming, Chen, Jin-Xian, Wang, Zheng, Liu, Qiang, Wang, Ji-Lin, Cai, Guo-Xiang, Chen, Ying-Xuan, Fang, Jing-Yuan
Format: Journal Article
Language:English
Published: Australia Wiley Subscription Services, Inc 01-10-2023
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Summary:Colorectal cancer (CRC) incidence has increased among patients aged <50 years. Exploring high-risk factors and screening high-risk populations may help lower early-onset CRC (EO-CRC) incidence. We developed noninvasive predictive models for EO-CRC and investigated its risk factors. This retrospective multicenter study collected information on 1756 patients (811 patients with EO-CRC and 945 healthy controls) from two medical centers in China. Sociodemographic features, clinical symptoms, medical and family history, lifestyle, and dietary factors were measured. Patients from one cohort were randomly assigned (8:2) to two groups for model establishment and internal validation, and another independent cohort was used for external validation. Multivariable logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost) were performed to establish noninvasive predictive models for EO-CRC. Some variables in the model influenced EO-CRC occurrence and were further analyzed. Multivariable logistic regression analysis yielded adjusted odd ratios (ORs) and 95% confidence intervals (CIs). All three models showed good performance, with areas under the receiver operator characteristic curves (AUCs) of 0.82, 0.84, and 0.82 in the internal and 0.78, 0.79, and 0.78 in the external validation cohorts, respectively. Consumption of sweet (OR 2.70, 95% CI 1.89-3.86, P < 0.001) and fried (OR 2.16, 95% CI 1.29-3.62, P < 0.001) foods ≥3 times per week was significantly associated with EO-CRC occurrence. We established noninvasive predictive models for EO-CRC and identified multiple nongenetic risk factors, especially sweet and fried foods. The model has good performance and can help predict the occurrence of EO-CRC in the Chinese population.
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content type line 23
ISSN:0815-9319
1440-1746
DOI:10.1111/jgh.16243