Establishment of a Dynamic Nomogram for Predicting the Risk of Lymph Node Metastasis in T1 Stage Colorectal Cancer

被引:5
|
作者
Liu, Zitao [1 ]
Huang, Chao [1 ]
Tian, Huakai [1 ]
Liu, Yu [1 ]
Huang, Yongshan [1 ]
Zhu, Zhengming [1 ]
机构
[1] Nanchang Univ, Dept Gastrointestinal Surg, Affiliated Hosp 2, Nanchang, Jiangxi, Peoples R China
来源
FRONTIERS IN SURGERY | 2022年 / 9卷
关键词
T1 stage colorectal cancer; lymph node metastasis (LNM); random forest; LASSO regression algorithm; dynamic nomogram; COLON-CANCER; ARTIFICIAL-INTELLIGENCE; COMPUTED-TOMOGRAPHY; SUBMUCOSAL INVASION; RECTAL-CANCER; CARCINOMA; COLONOSCOPY; GUIDELINES; MANAGEMENT; SURGERY;
D O I
10.3389/fsurg.2022.845666
中图分类号
R61 [外科手术学];
学科分类号
摘要
BackgroundAccurate prediction of the risk of lymph node metastasis in patients with stage T1 colorectal cancer is crucial for the formulation of treatment plans for additional surgery and lymph node dissection after endoscopic resection. The purpose of this study was to establish a predictive model for evaluating the risk of LNM in patients with stage T1 colorectal cancer. MethodsThe clinicopathological and imaging data of 179 patients with T1 stage colorectal cancer who underwent radical resection of colorectal cancer were collected. LASSO regression and a random forest algorithm were used to screen the important risk factors for LNM, and a multivariate logistic regression equation and dynamic nomogram were constructed. The C index, Calibration curve, and area under the ROC curve were used to evaluate the discriminant and prediction ability of the nomogram. The net reclassification index (NRI), comprehensive discriminant improvement index (IDI), and clinical decision curve (DCA) were compared with traditional ESMO criteria to evaluate the accuracy, net benefit, and clinical practicability of the model. ResultsThe probability of lymph node metastasis in patients with T1 colorectal cancer was 11.17% (20/179). Multivariate analysis showed that the independent risk factors for LNM in T1 colorectal cancer were submucosal invasion depth, histological grade, CEA, lymphovascular invasion, and imaging results. The dynamic nomogram model constructed with independent risk factors has good discrimination and prediction capabilities. The C index was 0.914, the corrected C index was 0.890, the area under the ROC curve was 0.914, and the accuracy, sensitivity, and specificity were 93.3, 80.0, and 91.8%, respectively. The NRI, IDI, and DCA show that this model is superior to the ESMO standard. ConclusionThis study establishes a dynamic nomogram that can effectively predict the risk of lymph node metastasis in patients with stage T1 colorectal cancer, which will provide certain help for the formulation of subsequent treatment plans for patients with stage T1 CRC after endoscopic resection.
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页数:12
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