ZhanShuo Liu,1,* Hao Liu,2,* Yue Zhang,3 YuHang Yang,4 Hongyu Gao1 

1Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin, People’s Republic of China; 2Department of Urology, The Third Affillated Hospital of Qiqihaer Medical University, Qiqihar Medical University, Qiqihar, People’s Republic of China; 3Yangtze University School of Medicine, Yangtze University, Jingzhou, People’s Republic of China; 4School of Computer and Information Engineering, Heilongjiang University of Science and Technology, Harbin, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Hongyu Gao, Email hydgaohongyu@163.com

Background: The prognostic discriminative ability of the pathological tumor-node-metastasis (pTNM) staging system for gastric cancer (GC) still requires further improvement. This study aimed to develop a pTNM-Inflammation (pTNM-I) staging system by integrating pTNM staging with peripheral inflammatory status to enhance the prognostic stratification capability of pTNM.
Methods: This study retrospectively analyzed 4,049 patients who underwent curative surgery for GC. Receiver Operating Characteristic (ROC) analysis was used to determine the optimal cutoff values of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) for different pTNM stages, and the pTNM-I staging system was constructed. Kaplan-Meier survival curves were used to evaluate the impact of pTNM-I on prognosis. Cox regression analysis was employed to identify independent risk factors affecting patient outcomes. Finally, a nomogram was constructed based on pTNM-I staging and clinical pathological characteristics.
Results: After constructing the pTNM-I staging system based on the optimal cutoff values of NLR, PLR, and SII, the 5-year survival rates for stages I-a to III-c were 97.6%, 88.0%, 84.2%, 92.5%, 77.5%, 71.3%, 74.3%, 45.3%, and 27.5% (P < 0.001). ROC analysis showed that the predictive ability of pTNM-I was superior to that of pTNM (AUC: 0.798 vs 0.743). Cox analysis revealed that pTNM-I was an independent prognostic factor associated with patient outcomes (P < 0.001). The nomogram based on pTNM-I also demonstrated better predictive performance compared to the traditional pTNM staging (AUC: 0.808 vs 0.743).
Conclusion: The pTNM-I staging system provided more robust prognostic discriminative ability. As a simple, economical, and routine prognostic tool, it is worthy of clinical application.

Keywords: gastric cancer, pTNM, inflammation, prognosis