Li LY, Kobayashi S, Murakami S, Yamaguchi S, Tasaki K, Eguchi S, Kanetaka K. Integrating inflammation-based scores into gastric cancer prognosis. World J Gastrointest Surg 2026; 18(1): 113363 [DOI: 10.4240/wjgs.v18.i1.113363]
Corresponding Author of This Article
Shinichiro Kobayashi, MD, PhD, Associate Professor, FACS, Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8501, Japan. skobayashi1980@gmail.com
Research Domain of This Article
Oncology
Article-Type of This Article
Editorial
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/
Lu-Yang Li, Shinichiro Kobayashi, Shunsuke Murakami, Shun Yamaguchi, Kaito Tasaki, Susumu Eguchi, Kengo Kanetaka, Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki 852-8501, Japan
Author contributions: Li LY and Kobayashi S drafted the manuscript; Li LY, Kobayashi S, Murakami S, Yamaguchi S, and Tasaki K edited the manuscript; Eguchi S and Kanetaka K conceived the study and supervised the overall design. All authors have read and approved the final manuscript.
Supported by Japan Society for the Promotion of Science, No. 24K11935.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
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: Shinichiro Kobayashi, MD, PhD, Associate Professor, FACS, Department of Surgery, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1 Sakamoto, Nagasaki 852-8501, Japan. skobayashi1980@gmail.com
Received: August 25, 2025 Revised: October 2, 2025 Accepted: November 3, 2025 Published online: January 27, 2026 Processing time: 151 Days and 2 Hours
Abstract
The conventional tumor-node-metastasis (TNM) staging system is crucial for predicting the prognosis of gastric cancer. However, TNM staging fails to delineate tumor biology and host immune responses. Zhou et al have addressed this in a noteworthy study, they analyzed a cohort of 1071 patients with stage I-III gastric cancer who had undergone radical gastrectomy. The systemic inflammation response index (SIRI) and platelet-to-lymphocyte ratio (PLR) score were derived from the SIRI and PLR. Multivariate analysis identified the SIRI-PLR score as an independent predictor of survival. This was significant along with factors such as age, tumor size, and TNM stage. Importantly, they created a nomogram that integrated these variables, demonstrating superior predictive accuracy compared to the TNM staging system. The findings of this single-center cohort study require prospective multicenter validation to confirm their reproducibility and generalizability. Furthermore, inflammatory markers are dynamic and serial measurements can offer a more refined assessment of patient prognoses and guide treatment responses. These findings should be combined with genomic, immunological, and radiomics data. This approach promises precise and personalized risk stratification, thereby improving the prediction of prognosis in patients with gastric cancer.
Core Tip: The conventional tumor-node-metastasis (TNM) staging system for gastric cancer has limitations as it often fails to capture tumor biology and host immune responses. Zhou et al developed a novel composite biomarker using the inflammatory markers, systemic inflammation response index and platelet-to-lymphocyte ratio. This score has been identified as an independent predictor of survival. A nomogram integrating this score with the TNM stage and other factors demonstrated superior predictive accuracy compared with the TNM system alone. Although promising, these findings require multicenter validation. Future studies should integrate these biomarkers with genomic data for more precise and personalized risk stratification of patients with gastric cancer.
