Nomogram established using risk factors of early gastric cancer for predicting the lymph node metastasis

被引:1
作者
Jiang, Xiao-Cong [1 ]
Yao, Xiao-Bing [2 ]
Xia, Heng-Bo [3 ]
Su, Ye-Zhou [4 ]
Luo, Pan-Quan [3 ]
Sun, Jian-Ran [5 ]
Song, En-Dong [3 ]
Wei, Zhi-Jian [3 ]
Xu, A-Man [3 ]
Zhang, Li-Xiang [3 ,6 ]
Lan, Yu-Hong [1 ,7 ]
机构
[1] Huizhou Municipal Cent Hosp, Dept Radiotherapy Oncol, Huizhou 516001, Guangdong, Peoples R China
[2] Shanghai Seventh Peoples Hosp, Emergency Surg, Shanghai 200137, Peoples R China
[3] Anhui Med Univ, Affiliated Hosp 1, Dept Gen Surg, Hefei 230031, Anhui, Peoples R China
[4] Anhui Med Univ, Affiliated Hosp 1, Dept Obstet & Gynecol, Hefei 230031, Anhui, Peoples R China
[5] USTC, Affiliated Hosp 1, Dept Endocrinol, Div Life Sci & Med, Hefei 230031, Anhui, Peoples R China
[6] Anhui Med Univ, Affiliated Hosp 1, Dept Gastroenterol, Hefei 230031, Anhui, Peoples R China
[7] Huizhou Municipal Cent Hosp, Dept Radiotherapy Oncol, 41 Eling North Rd, Huizhou 516001, Guangdong, Peoples R China
关键词
SEER; Early gastric cancer; Lymph node metastasis; Risk factors; Nomogram; ENDOSCOPIC SUBMUCOSAL DISSECTION; HELICOBACTER-PYLORI; PROGNOSTIC VALUE; YOUNG;
D O I
10.4251/wjgo.v15.i4.665
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BACKGROUND: For the prognosis of patients with early gastric cancer (EGC), lymph node metastasis (LNM) plays a crucial role. A thorough and precise evaluation of the patient for LNM is now required.AIM: To determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients.METHODS: Clinical information and pathology data of 2217 EGC patients downloaded from the Surveillance, Epidemiology, and End Results database were collected and analyzed. Based on a 7:3 ratio, 1550 people were categorized into training sets and 667 people were assigned to testing sets, randomly. Based on the factors influencing LNM determined by the training sets, the nomogram was drawn and verified.RESULTS; Based on multivariate analysis, age at diagnosis, histology type, grade, T-stage, and size were risk factors of LNM for EGC. Besides, nomogram was drawn to predict the risk of LNM for EGC patients. Among the categorical variables, the effect of grade (well, moderate, and poor) was the most significant prognosis factor. For training sets and testing sets, respectively, area under the receiver-operating characteristic curve of nomograms were 0.751 [95% confidence interval (CI): 0.721-0.782] and 0.786 (95%CI: 0.742-0.830). In addition, the calibration curves showed that the prediction model of LNM had good consistency.CONCLUSION: Age at diagnosis, histology type, grade, T-stage, and tumor size were independent variables for LNM in EGC. Based on the above risk factors, prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.
引用
收藏
页码:665 / 676
页数:12
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