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Updated: Jun 21, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
A risk-prediction score about colorectal lesions based on the Chinese population of high-risk participants aged 50-65
1School of Medicine, Nankai University, Tianjin, China; Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China.
Objectives:
The present study aims to develop an effective risk-prediction score (RPS) to improve screening efficiency and contribute to secondary prevention of colorectal cancer (CRC).
Study Design:
Screening for colorectal lesions.
Methods:
14,398 high-risk individuals aged 50-65 years were included. The baseline characteristics of participants with and without colorectal lesions (CL) were compared using a Chi-squared test. The overall population was randomly split into a training set and a test set in the ratio of 80% and 20%. One-factor and multifactor logistic regression analyses were performed in the training set to construct the RPS (scores of 0-9.62). Area under curve (AUC) was calculated as an estimate of predictive performance using the receiver-operating characteristic (ROC) curve in the test set.
Results:
In the study population, being male, advanced age, current or previous smoking, weekly alcohol consumption, high body mass index (BMI ≥24 kg/m2), and previously detected colonic polyp were associated with higher risk of CL. Compared to the low-risk group (0-2.31 points), the ORs and 95% confidence intervals (CIs) for the moderate-risk group (2.31-3.85 points) and high-risk group (3.85-8.42 points) were 1.58 (1.44, 1.73) and 2.52 (2.30, 2.76), respectively. For every 1-point increase in score, participants had a 27% increased risk of CL (OR:1.27, 95% CI: 1.24, 1.30). For participants with CL predicted by RPS, the area under the working characteristic curve was 0.61 (P < 0.001).
Conclusion:
Our RPS can quickly and efficiently identify multiple lesions of the colorectum. Combining RPS with existing screening strategies facilitates the identification of very high-risk individuals and may help to prevent CRC.

