Retrospective Cohort Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jun 28, 2023; 29(24): 3807-3824
Published online Jun 28, 2023. doi: 10.3748/wjg.v29.i24.3807
Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study
Jia-Jia Yang, Xiao-Yong Wang, Rui Ma, Mei-Hong Chen, Guo-Xin Zhang, Xuan Li
Jia-Jia Yang, Mei-Hong Chen, Guo-Xin Zhang, Xuan Li, Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
Xiao-Yong Wang, Department of Gastroenterology, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou 213000, Jiangsu Province, China
Rui Ma, Department of Nursing, Jiangsu Health Vocational College, Nanjing 211800, Jiangsu Province, China
Author contributions: Yang JJ, Wang XY, Ma R and Chen MH contributed equally to this work; Yang JJ and Wang XY designed the research study and performed the research; Ma R and Chen MH contributed new reagents and analytic tools; Yang JJ, Wang XY, Ma R and Chen MH analyzed the data and wrote the manuscript; all authors have read and approve the final manuscript.
Supported by National Natural Science Foundation of China, No. 82200625 and No. 82100595; Youth Talent Development Program, No. YNRCQN0313; Young Scholar Fostering Fund of the First Affiliated Hospital of Nanjing Medical University, No. PY2021023; Top Talent of Changzhou “The 14th Five-Year Plan” High-Level Health Talents Training Project, No. 2022CZBJ051; and Natural Science Foundation of Jiangsu Province, China, No. BK20210958.
Institutional review board statement: The study was reviewed and approved by the Medical Ethics Committee of the First Affiliated Hospital of Nanjing Medical University and the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University (Approval No. 2021KY311-01).
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xuan Li, PhD, Attending Doctor, Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing 210029, Jiangsu Province, China. lixuan20091225@163.com
Received: February 2, 2023
Peer-review started: February 2, 2023
First decision: March 20, 2023
Revised: March 30, 2023
Accepted: May 16, 2023
Article in press: May 16, 2023
Published online: June 28, 2023
Processing time: 145 Days and 21.4 Hours
Abstract
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 Em-powerStats 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.

Keywords: Early gastric cancer; Signet-ring cell carcinoma; Lymph node metastasis; Nomogram; Prediction model

Core Tip: By establishing and comparing prediction models of lymph node metastasis (LNM) in early gastric cancer, we found that artificial neural network model was better than logistic regression model in sensitivity and accuracy. Among 249 signet-ring cell carcinoma (SRCC) patients, LNM was more common in mixed than in pure SRCC. A validated prediction model was also developed to recognize the risk for LNM in early gastric SRCC, which can be used to help make decisions regarding treatment of patients before performing surgery.