• Jing-Yuan Xu, Ya-Tao Wang, Xiao-Ling Li, Yong Shao, Zhi-Yi Han, Jie Zhang, Long-Bao Yang, Jiang Deng, Ting Li, Ting Wu, Xiao-Lan Lu, and Yan Cheng.
• Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China.
• Am. J. Med. Sci. 2022 Jul 1; 364 (1): 59-65.

BackgroundIn China, health screening has become common, although colonoscopy is not always available or acceptable. We sought to develop a prediction model of colorectal cancer (CRC) for health screening population based on readily available clinical data to reduce labor and economic costs.MethodsWe conducted a cross-sectional study based on a health screening population in Karamay Central Hospital. By collecting clinical data and basic information from participants, we identified independent risk factors and established a prediction model of CRC. Internal and external validation, calibration plot, and decision curve analysis were employed to test discriminating ability, calibration ability, and clinical practicability.ResultsIndependent risk factors of CRC, which were readily available in primary public health institutions, included high-density lipoprotein cholesterol, male sex, total cholesterol, advanced age, and hemoglobin. These factors were successfully incorporated into the prediction model (AUC 0.740, 95% CI 0.713-0.767). The model demonstrated a high degree of discrimination and calibration, in addition to a high degree of clinical practicability in high-risk people.ConclusionsThe prediction model exhibits good discrimination and calibration and is pragmatic for CRC screening in rural areas and primary public health institutions.Copyright © 2022. Published by Elsevier Inc.

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