Sun N, Tan BB, Li Y. Nomogram model including LATS2 expression was constructed to predict the prognosis of advanced gastric cancer after surgery. World J Gastrointest Surg 2024; 16(2): 518-528 [PMID: 38463354 DOI: 10.4240/wjgs.v16.i2.518]
Corresponding Author of This Article
Yong Li, PhD, Chief Doctor, Professor, Third Department of General Surgery, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Chang'an District, Shijiazhuang 050011, Hebei Province, China. liyong780728@163.com
Research Domain of This Article
Oncology
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/
World J Gastrointest Surg. Feb 27, 2024; 16(2): 518-528 Published online Feb 27, 2024. doi: 10.4240/wjgs.v16.i2.518
Nomogram model including LATS2 expression was constructed to predict the prognosis of advanced gastric cancer after surgery
Nan Sun, Bi-Bo Tan, Yong Li
Nan Sun, Department of Blood Transfusion, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, Hubei Province, China
Bi-Bo Tan, Yong Li, Third Department of General Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang 050011, Hebei Province, China
Author contributions: Sun N designed the research study; Sun N, Tan BB and Li Y performed the research; Sun N and Tan BB contributed analytic tools; Sun N and Li Y analyzed the data and wrote the manuscript; all authors have read and approve the final manuscript.
Institutional review board statement: This was a retrospective study approved by the Ethics Committee of the Fourth Hospital of Hebei Medical University (Approval No. 2019ME0039).
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: All authors claim no conflicts of interest.
Data sharing statement: Raw data, statistical codes and datasets are available from the corresponding author.
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: Yong Li, PhD, Chief Doctor, Professor, Third Department of General Surgery, The Fourth Hospital of Hebei Medical University, No. 12 Jiankang Road, Chang'an District, Shijiazhuang 050011, Hebei Province, China. liyong780728@163.com
Received: December 12, 2023 Peer-review started: December 12, 2023 First decision: January 2, 2024 Revised: January 13, 2024 Accepted: January 24, 2024 Article in press: January 24, 2024 Published online: February 27, 2024
ARTICLE HIGHLIGHTS
Research background
Gastric cancer is a significant global health concern, ranking fifth in incidence and fourth in mortality among all cancers. The prognosis is often poor due to late-stage diagnosis. Molecular signaling pathways and gene mutations, like those involving the LATS gene, play a crucial role in the pathogenesis of gastric cancer, affecting prognosis and treatment options.
Research motivation
There is a need for more accurate prognostic models for advanced gastric cancer that can incorporate molecular biomarkers like LATS2 expression. This would improve individual prognosis assessments and aid in personalizing treatment strategies.
Research objectives
The objective of this research is to construct a nomogram model based on LATS2 expression and evaluate its predictive accuracy for the survival prognosis of patients with advanced gastric cancer post-surgery.
Research methods
The study retrospectively analyzed clinical data of 245 advanced gastric cancer patients, dividing them into a training group and a validation group. Univariate and multivariate Cox regression analyses were used to assess the prognostic value of LATS2 expression. The model's performance was analyzed through various statistical methods including C-index, receiver operating characteristic curves, calibration curves, and decision curves.
Research results
The nomogram model demonstrated high C-indexes and area under curve values, indicating strong predictive accuracy. Calibration plots showed high agreement between predicted and actual survival, and decision curves indicated the model's superior net benefit over tumor-node-metastasis (TNM) staging alone.
Research conclusions
The nomogram model incorporating LATS2 expression provided significant clinical value in predicting the postoperative prognosis of advanced gastric cancer patients. It showed superior discrimination and net clinical benefit compared to TNM staging alone.
Research perspectives
The study suggests that the developed model can assist in clinical decision-making, but acknowledges limitations such as the small, single-center sample size. Future research should aim at external validation and include more comprehensive clinical and molecular data to optimize prognostic accuracy.
