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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Gastrointestinal Cancers: Gastric and Esophageal Cancers
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1473798

Prognostic prediction and treatment options for gastric signet ring cell carcinoma: A SEER database analysis

Provisionally accepted
Chengqing Yu Chengqing Yu 1Jian Yang Jian Yang 1*Haoran Li Haoran Li 2Jie Wang Jie Wang 1*Kanghui Jin Kanghui Jin 1*Yifan Li Yifan Li 1*Zixiang Zhang Zixiang Zhang 1*Jian Zhou Jian Zhou 1*Yuchen Tang Yuchen Tang 1*
  • 1 The First Affiliated Hospital of Soochow University, Suzhou, China
  • 2 Department of Gastrointestinal Surgery, Changzhou No.2 People's Hospital, Changzhou, China

The final, formatted version of the article will be published soon.

    In recent years, the overall incidence of gastric cancer has decreased. However, the incidence of gastric signet ring cell carcinoma (SRCC) is still increasing year by year. Compared with other subtypes (non-SRCC) such as adenocarcinoma, SRCC usually exhibits a more aggressive biological behaviour. Therefore, studying the prognostic differences and factors associated with SRCC is essential to improve the accuracy of diagnosis and prognosis. The purpose of this study was to investigate the prognostic factors influencing the prognosis of patients with SRCC and to develop personalised treatments for different subgroups of patients.The data on gastric SRCC patients and gastric adenocarcinoma (AC) patients from 1992 to 2020 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The data of gastric SRCC as the external validation group was reviewed from the First Affiliated Hospital of Soochow University. The overall survival (OS) and cancer specific survival (CSS) at 1 and 2 years were predicted for SRCC patients by constructing prognostic nomograms. A series of validation methods, including Akaike information criterion (AIC), decision curve analysis (DCA), calibration curve analysis, the concordance index (C-index) and the area under the receiver operating characteristic (AUC) curve, were used to verify the accuracy and reliability of the models. Results In all, 549 patients with SRCC were included after propensity score matching (PSM). Multivariate Cox regression analysis showed that T stage, N stage, M stage and surgical approach were independent risk factors affecting the prognosis of SRCC patients. A prognostic nomogram was constructed and validated as an accurate model for SRCC patients after scoring by receiver operating characteristic curve (ROC) curves and calibration plots. The patients were further divided into highrisk and low-risk groups, and the Kaplan-Meier curves showed that SRCC patients in the low-risk group could receive only surgery without chemotherapy, while chemotherapy plus surgery was a better option for SRCC patients in the high-risk group.The prognosis for SRCC was less favorable than that of AC in terms of CSS. The nomograms were developed and validated to predict OS and CSS in patients with SRCC, helping in developing appropriate individualized treatment schedules.

    Keywords: gastric cancer, Signet ring cell carcinoma, SEER database, nomogram, Survival

    Received: 31 Jul 2024; Accepted: 02 Oct 2024.

    Copyright: © 2024 Yu, Yang, Li, Wang, Jin, Li, Zhang, Zhou and Tang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Jian Yang, The First Affiliated Hospital of Soochow University, Suzhou, China
    Jie Wang, The First Affiliated Hospital of Soochow University, Suzhou, China
    Kanghui Jin, The First Affiliated Hospital of Soochow University, Suzhou, China
    Yifan Li, The First Affiliated Hospital of Soochow University, Suzhou, China
    Zixiang Zhang, The First Affiliated Hospital of Soochow University, Suzhou, China
    Jian Zhou, The First Affiliated Hospital of Soochow University, Suzhou, China
    Yuchen Tang, The First Affiliated Hospital of Soochow University, Suzhou, China

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