Development of a Nomogram to Predict Postoperative Peritoneal Metastasis of Colon Cancer

Jie Dai,Ke-Xin Wang, Ling-Yu Wu, Xiao-Han Bai,Hong-Yuan Shi,Qing Xu,Jing Yu

JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY(2023)

引用 0|浏览2
暂无评分
摘要
Objective The aim of this study was to determine the clinicopathological and radiological risk factors for postoperative peritoneal metastasis and develop a prediction model for the early detection of peritoneal metastasis in patients with colon cancer.Methods We included 174 patients with colon cancer. The clinicopathological and radiological data were retrospectively analyzed. A Cox proportional hazards regression model was used to identify risk factors for postoperative peritoneal metastasis. Based on these risk factors, a nomogram was developed.Results At a median follow-up of 63 months, 43 (24.7%) patients developed peritoneal metastasis. Six independent risk factors (hazards ratio [95% confidence interval]) were identified for postoperative peritoneal metastasis: abdominopelvic fluid (2.12 [1.02-4.40]; P = 0.04), longer maximum tumor length (1.02 [1.00-1.03]; P = 0.02), pN1 (2.50 [1.13-5.56]; P = 0.02), pN2 (4.45 [1.77-11.17]; P = 0.02), nonadenocarcinoma (2.75 [1.18-6.38]; P = 0.02), and preoperative carcinoembryonic antigen levels >= 5 ng/mL (3.08 [1.50-6.30]; P < 0.01). A clinicopathological-radiological model was developed based on these factors. The model showed good discrimination (concordance index, 0.798 [0.723-0.876]; P < 0.001) and was well-calibrated.Conclusions The developed clinicopathological-radiological nomogram may assist clinicians in identifying patients at high risk of postoperative peritoneal metastasis.
更多
查看译文
关键词
colon cancer,postoperative peritoneal metastasis,predictive model,risk factor
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要