Tsai Tzong-Yun, You Jeng-Fu, Hsu Yu-Jen, Jhuang Jing-Rong, Chern Yih-Jong, Hung Hsin-Yuan, Yeh Chien-Yuh, Hsieh Pao-Shiu, Chiang Sum-Fu, Lai Cheng-Chou, Chiang Jy-Ming, Tang Reiping, Tsai Wen-Sy
Division of Colon and Rectal Surgery, Department of Surgery, Chang Gung Memorial Hospital at Linkou, Taoyuan City 33305, Taiwan.
College of Medicine, Chang Gung University, Taoyuan City 33305, Taiwan.
Cancers (Basel). 2021 Jun 4;13(11):2808. doi: 10.3390/cancers13112808.
(1) Background: The aim of this study was to develop a prediction model for assessing individual mPC risk in patients with pT4 colon cancer. Methods: A total of 2003 patients with pT4 colon cancer undergoing R0 resection were categorized into the training or testing set. Based on the training set, 2044 Cox prediction models were developed. Next, models with the maximal C-index and minimal prediction error were selected. The final model was then validated based on the testing set using a time-dependent area under the curve and Brier score, and a scoring system was developed. Patients were stratified into the high- or low-risk group by their risk score, with the cut-off points determined by a classification and regression tree (CART). (2) Results: The five candidate predictors were tumor location, preoperative carcinoembryonic antigen value, histologic type, T stage and nodal stage. Based on the CART, patients were categorized into the low-risk or high-risk groups. The model has high predictive accuracy (prediction error ≤5%) and good discrimination ability (area under the curve >0.7). (3) Conclusions: The prediction model quantifies individual risk and is feasible for selecting patients with pT4 colon cancer who are at high risk of developing mPC.
(1) 背景：本研究旨在开发一种预测模型，用于评估pT4期结肠癌患者发生远处转移（mPC）的个体风险。方法：将总共2003例接受R0切除的pT4期结肠癌患者分为训练集或测试集。基于训练集，开发了2044个Cox预测模型。接下来，选择具有最大C指数和最小预测误差的模型。然后使用曲线下时间依赖面积和Brier评分基于测试集对最终模型进行验证，并开发了一个评分系统。根据风险评分将患者分层为高风险组或低风险组，截断点由分类回归树（CART）确定。(2) 结果：五个候选预测因素为肿瘤位置、术前癌胚抗原值、组织学类型、T分期和淋巴结分期。基于CART，将患者分为低风险组或高风险组。该模型具有较高的预测准确性（预测误差≤5%）和良好的鉴别能力（曲线下面积>0.7）。(3) 结论：该预测模型可量化个体风险，对于选择有发生mPC高风险的pT4期结肠癌患者是可行的。
