A nomogram for predicting lymph node metastasis in early gastric cancer.
10.3760/cma.j.cn441530-20210208-00059
- Author:
Hao CUI
1
;
Bo CAO
2
;
Huan DENG
2
;
Gui Bin LIU
1
;
Wen Quan LIANG
2
;
Tian Yu XIE
1
;
Lu YE
1
;
Qing Peng ZHANG
2
;
Ning WANG
2
;
Fei De LIU
3
;
Bo WEI
2
Author Information
1. Department of General Surgery & Instituteof General Surgery, Chinese PLA General Hospital First Medical Center, Beijing 100853, China School of Medicine, Nankai University, Tianjin 300071, China.
2. Department of General Surgery & Instituteof General Surgery, Chinese PLA General Hospital First Medical Center, Beijing 100853, China.
3. Departmentof General Surgery, Chinese PLA General Hospital Fourth Medical Center, Beijing 100048, China.
- Publication Type:Journal Article
- Keywords:
Lymph node metastasis;
Nomogram;
Risk factor;
Stomach neoplasms, early stage
- MeSH:
Female;
Gastrectomy;
Humans;
Lymph Node Excision;
Lymph Nodes;
Lymphatic Metastasis;
Nomograms;
Retrospective Studies;
Risk Factors;
Stomach Neoplasms/surgery*
- From:
Chinese Journal of Gastrointestinal Surgery
2022;25(1):40-47
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To explore the independent risk factors of lymph node metastasis (LNM) in early gastric cancer, and to use nomogram to construct a prediction model for above LNM. Methods: A retrospective cohort study was conducted. Inclusion criteria: (1) primary early gastric cancer as stage pT1 confirmed by postoperative pathology; (2) complete clinicopathological data. Exclusion criteria: (1) patients with advanced gastric cancer, stump gastric cancer or history of gastrectomy; (2) early gastric cancer patients confirmed by pathology after neoadjuvant chemotherapy; (3) other types of gastric tumors, such as lymphoma, neuroendocrine tumor, stromal tumor, etc.; (4) primary tumors of other organs with gastric metastasis. According to the above criteria, 1633 patients with early gastric cancer who underwent radical gastrectomy at the Department of General Surgery of the Chinese PLA General Hospital First Medical Center from December 2005 to December 2020 were enrolled as training set, meanwhile 239 patients with early gastric cancer who underwent gastrectomy at the Department of General Surgery of the Chinese PLA General Hospital Fourth Medical Center from December 2015 to December 2020 were enrolled as external validation set. Risk factors of LNM in early gastric cancer were identified by using univariate and multivariate logistic regression analyses. A nomogram prediction model was established with significant factors screened by multivariate analysis. Area under the receiver operating characteristic curve (AUC) was used for assessing the predictive value of the model. Calibration curve was drawn for external validation. Results: Among 1633 patients in training set, the mean number of retrieved lymph nodes was 20 (13-28), and 209 patients (12.8%) had lymph node metastasis. Univariate analysis showed that gender, resection range, tumor location, tumor morphology, lymph node clearance, vascular invasion, lymphatic cancer thrombus, tumor length, tumor differentiation, microscopic presence of signet ring cells and depth of tumor invasion were associated with LNM (all P<0.05). Multivariate analysis revealed that females, tumor morphology as ulcer type, vascular invasion, lymphatic cancer thrombus, tumor length≥3 cm, deeper invasion of mucosa, and poor differentiation were independent risk factors for LNM in early gastric cancers (all P<0.05). Receiver operating characteristic curve indicated that AUC of training set was 0.818 (95%CI: 0.790-0.847) and AUC of external validation set was 0.765 (95%CI: 0.688-0.843). The calibration curve showed that the LNM probability predicted by nomogram was consistent with the actual situation (C-index: 0.818 in training set and 0.765 in external validation set). Conclusions: Females, tumor morphology as ulcer type, vascular invasion, lymphatic cancer thrombus, tumor length≥3 cm, deeper invasion of mucosa and poor differentiation are independent risk factors for LNM of early gastric cancer. The establishment of a nomogram prediction model for LNM in early gastric cancer has great diagnostic value and can provide reference for treatment selection.
