Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study

被引:3
作者
Yang, Jia-Jia [1 ]
Wang, Xiao-Yong [2 ]
Ma, Rui [3 ]
Chen, Mei-Hong [1 ]
Zhang, Guo-Xin [1 ]
Li, Xuan [1 ]
机构
[1] Nanjing Med Univ, Dept Gastroenterol, Affiliated Hosp 1, Nanjing 210029, Jiangsu, Peoples R China
[2] Nanjing Med Univ, Dept Gastroenterol, Affiliated Changzhou Peoples Hosp 2, Changzhou 213000, Jiangsu, Peoples R China
[3] Jiangsu Hlth Vocat Coll, Dept Nursing, Nanjing 211800, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Early gastric cancer; Signet-ring cell carcinoma; Lymph node metastasis; Nomogram; Prediction model; RISK-FACTORS; HISTOLOGY; CANCER; IMPACT; SURVIVAL;
D O I
10.3748/wjg.v29.i24.3807
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
BACKGROUND Signet-ring cell carcinoma (SRCC) was previously thought to have a worse prognosis than other differentiated gastric cancer (GC), however, recent studies have shown that the prognosis of SRCC is related to pathological type. We hypothesize that patients with SRCC and with different SRCC pathological components have different probability of lymph node metastasis (LNM). AIM To establish models to predict LNM in early GC (EGC), including early gastric SRCC. METHODS Clinical data from EGC patients who had undergone gastrectomy at the First Affiliated Hospital of Nanjing Medical University from January 2012 to March 2022 were reviewed. The patients were divided into three groups based on type: Pure SRCC, mixed SRCC, and non-signet ring cell carcinoma (NSRC). The risk factors were identified through statistical tests using SPSS 23.0, R, and EmpowerStats software. RESULTS A total of 1922 subjects with EGC were enrolled in this study, and included 249 SRCC patients and 1673 NSRC patients, while 278 of the patients (14.46%) presented with LNM. Multivariable analysis showed that gender, tumor size, depth of invasion, lymphovascular invasion, ulceration, and histological subtype were independent risk factors for LNM in EGC. Establishment and analysis using prediction models of EGC showed that the artificial neural network model was better than the logistic regression model in terms of sensitivity and accuracy (98.0% vs 58.1%, P = 0.034; 88.4% vs 86.8%, P < 0.001, respectively). Among the 249 SRCC patients, LNM was more common in mixed (35.06%) rather than in pure SRCC (8.42%, P < 0.001). The area under the ROC curve of the logistic regression model for LNM in SRCC was 0.760 (95%CI: 0.682-0.843), while the area under the operating characteristic curve of the internal validation set was 0.734 (95%CI: 0.643-0.826). The subgroups analysis of pure types showed that LNM was more common in patients with a tumor size > 2 cm (OR = 5.422, P = 0.038). CONCLUSION A validated prediction model was developed to recognize the risk of LNM in EGC and early gastric SRCC, which can aid in pre-surgical decision making of the best method of treatment for patients. (c) The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
引用
收藏
页码:3807 / 3824
页数:18
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