Department of Oncology, Binzhou Medical University Hospital, No. 661, Yellow-River Second Street, Binzhou, 256600, Shandong, China.
School of Clinical Medicine, Tsinghua University, Beijing, 100084, China.
Tech Coloproctol. 2024 Aug 14;28(1):107. doi: 10.1007/s10151-024-02986-4.
Total neoadjuvant therapy (TNT) has been recommended by the National Comprehensive Cancer Network for treating locally advanced rectal cancer (LARC), but extremely rare studies have focused on establishing nomograms to predict the prognosis in these patients after TNT. We aimed to develop a nomogram to predict overall survival (OS) in rectal cancer patients who underwent TNT.
In retrospective cohort study, we extract the data of the rectal cancer patients from the SEER database between 2010 and 2015, including demographic information and tumor characteristics. The cohort was divided into training set and validation set based on a ratio of 7:3. Univariate logistic regression analysis was utilized for the comparison of variables in training set. Candidate variables with P < 0.1 in training set was entered into the best subset selection, LASSO regression and Boruta feature selection. Finally, the selected variables significantly associated with the 3-year, 5-year, and 8-year OS were used to build a nomogram, followed by validation using receiver operating characteristic (ROC) curve, area under the curve (AUC), and calibration curve.
A total of 3265 rectal cancer patients (training set: 2285; test set: 980) were included in the present study. A nomogram was developed to predict the 3-year, 5-year, and 8-year OS based on age, household income, total number of in situ/malignant tumors, CEA, T stage, N stage and perineural invasion. The nomogram showed good efficiency in predicting the 3-year, 5-year and 8-year OS with good AUC for the training set and test set, respectively.
We established a nomogram for predicting the 3-year, 5-year, and 8-year OS of the rectal cancer patients, which showed good prediction efficiency for the OS after TNT.
美国国家综合癌症网络推荐对局部晚期直肠癌（LARC）患者进行新辅助放化疗（TNT），但鲜有研究致力于建立预测 TNT 后患者预后的列线图。我们旨在建立预测接受 TNT 的直肠癌患者总生存期（OS）的列线图。
在回顾性队列研究中，我们从 SEER 数据库中提取 2010 年至 2015 年期间直肠癌患者的数据，包括人口统计学信息和肿瘤特征。队列根据 7:3 的比例分为训练集和验证集。利用单因素 logistic 回归分析比较训练集中变量的差异。在训练集中 P<0.1 的候选变量进入最佳子集选择、LASSO 回归和 Boruta 特征选择。最后，将与 3 年、5 年和 8 年 OS 显著相关的选定变量用于构建列线图，然后使用接受者操作特征（ROC）曲线、曲线下面积（AUC）和校准曲线进行验证。
本研究共纳入 3265 例直肠癌患者（训练集：2285 例；验证集：980 例）。基于年龄、家庭收入、原位/恶性肿瘤总数、CEA、T 分期、N 分期和神经周围侵犯，建立了预测 3 年、5 年和 8 年 OS 的列线图。该列线图在预测 3 年、5 年和 8 年 OS 方面具有良好的效能，在训练集和验证集的 AUC 均较好。
我们建立了预测直肠癌患者 3 年、5 年和 8 年 OS 的列线图，该列线图对 TNT 后 OS 具有良好的预测效能。
