Liu W, Wu HY, Lin JX, Qu ST, Gu YJ, Zhu JZ, Xu CF. Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients. World J Gastrointest Oncol 2024; 16(8): 3507-3520 [PMID: 39171165 DOI: 10.4251/wjgo.v16.i8.3507]
Corresponding Author of This Article
Chun-Fang Xu, PhD, Chief Physician, Professor, Department of Gastroenterology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou 215006, Jiangsu Province, China. xuchunfang@suda.edu.cn
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
Wen Liu, Department of Gastroenterology, Changzhou Hospital of Traditional Chinese Medicine, Changzhou 213000, Jiangsu Province, China
Hong-Yu Wu, Jia-Xi Lin, Shu-Ting Qu, Jin-Zhou Zhu, Chun-Fang Xu, Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China
Yi-Jie Gu, Department of Gastroenterology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou 215200, Jiangsu Province, China
Author contributions: Liu W and Wu HY wrote the first draft of the manuscript; Qu ST and Gu YJ contributed to clinical data collection; Liu W, Lin JX, and Zhu JZ contributed to data analysis and results interpretation; Zhu JZ and Xu CF revised the manuscript; and all authors had checked and approved the final manuscript.
Supported bythe Science and Technology Plan of Suzhou City, No. SKY2021038.
Institutional review board statement: This study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (Number: 2024-145).
Informed consent statement: Patients were not required to give informed consent to the study because we had acquired the Ethics committee’s approval of exemption of the subject’s informed consent. This study does not have direct contact with the subjects, and only collects clinical baseline data from outpatient and inpatient medical records. the study results will remove any characters with the subjects’ identification to ensure that personal privacy will not be disclosed. Therefore, objectively, there will be no risk to the subjects.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Data will be made available on reasonable request.
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: Chun-Fang Xu, PhD, Chief Physician, Professor, Department of Gastroenterology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou 215006, Jiangsu Province, China. xuchunfang@suda.edu.cn
Received: March 28, 2024 Revised: May 14, 2024 Accepted: June 12, 2024 Published online: August 15, 2024 Processing time: 132 Days and 16 Hours
Abstract
BACKGROUND
Lymph node ratio (LNR) was demonstrated to play a crucial role in the prognosis of many tumors. However, research concerning the prognostic value of LNR in postoperative gastric neuroendocrine neoplasm (NEN) patients was limited.
AIM
To explore the prognostic value of LNR in postoperative gastric NEN patients and to combine LNR to develop prognostic models.
METHODS
A total of 286 patients from the Surveillance, Epidemiology, and End Results database were divided into the training set and validation set at a ratio of 8:2. 92 patients from the First Affiliated Hospital of Soochow University in China were designated as a test set. Cox regression analysis was used to explore the relationship between LNR and disease-specific survival (DSS) of gastric NEN patients. Random survival forest (RSF) algorithm and Cox proportional hazards (CoxPH) analysis were applied to develop models to predict DSS respectively, and compared with the 8th edition American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging.
RESULTS
Multivariate analyses indicated that LNR was an independent prognostic factor for postoperative gastric NEN patients and a higher LNR was accompanied by a higher risk of death. The RSF model exhibited the best performance in predicting DSS, with the C-index in the test set being 0.769 [95% confidence interval (CI): 0.691-0.846] outperforming the CoxPH model (0.744, 95%CI: 0.665-0.822) and the 8th edition AJCC TNM staging (0.723, 95%CI: 0.613-0.833). The calibration curves and decision curve analysis (DCA) demonstrated the RSF model had good calibration and clinical benefits. Furthermore, the RSF model could perform risk stratification and individual prognosis prediction effectively.
CONCLUSION
A higher LNR indicated a lower DSS in postoperative gastric NEN patients. The RSF model outperformed the CoxPH model and the 8th edition AJCC TNM staging in the test set, showing potential in clinical practice.
Core Tip: The prognostic value of lymph node ratio (LNR) in postoperative gastric neuroendocrine neoplasm (NEN) patients was explored in this research. A higher LNR indicated a lower disease-specific survival (DSS) in postoperative gastric NEN patients. In addition, we combined LNR to develop prognostic models to predict DSS for postoperative gastric NEN patients, using the random survival forest (RSF) algorithm and Cox proportional hazards (CoxPH) analysis. The RSF model outperformed the CoxPH model and the 8th edition American Joint Committee on Cancer tumor-node-metastasis staging in the test set. Also, the RSF model demonstrated value in risk stratification and individual prognosis prediction.
