Novel inflammatory-nutritional prognostic index for advanced gastric cancer patients undergoing gastrectomy and prophylactic hyperthermic intraperitoneal chemotherapy

• Published in: World journal of gastrointestinal surgery Vol. 17; no. 5; p. 102201
• Main Authors: Wang, Liang, Chen, Mei-Zhu, Liu, Lei, Jiang, Zi-Nian, Zhang, Si-Meng, Zhang, Mao-Shen, Zhang, Xian-Xiang, Liu, Rui-Qing, Wang, Dong-Sheng
• Format: Journal Article
• Language: English
• Published: United States Baishideng Publishing Group Inc 27.05.2025
• Subjects: Retrospective Study; Hyperthermic intraperitoneal chemotherapy; Inflammation; Prognosis; Nutrition; Gastric cancer; Nomogram
• DOI: 10.4240/wjgs.v17.i5.102201
• ISSN: 1948-9366

BACKGROUND Prophylactic hyperthermic intraperitoneal chemotherapy (HIPEC) is one of the methods to prevent peritoneal metastasis of advanced gastric cancer (AGC). However, the prognosis of gastric cancer patients who receive this treatment are different. AIM To investigate whether inflammation and nutritional indicators affect the prognosis of AGC patients undergoing gastrectomy and prophylactic HIPEC, and to develop a novel inflammatory nutritional prognostic index (INPI). Additionally, we aimed to construct a nomogram model to visually predict the prognosis of these patients and provide more accurate guidance for clinical decision-making. METHODS Clinical data from 181 Locally AGC patients who underwent gastrectomy and prophylactic HIPEC treatment at The Affiliated Hospital of Qingdao University were retrospectively collected. Multicollinearity analysis and least absolute shrinkage and selection operator (LASSO) Cox regression were utilized to construct the INPI. Survival analyses were performed using the Kaplan-Meier method and log-rank test. Both univariate and multivariate Cox proportional hazards regression models were used to analyze independent prognostic factors, and a prognostic nomogram was generated. And the model was validated using the bootstrap method. RESULTS Clinical data from 181 locally AGC patients who underwent gastrectomy and prophylactic HIPEC treatment at The Affiliated Hospital of Qingdao University were retrospectively collected. Multicollinearity analysis and LASSO Cox regression were utilized to construct the INPI. Survival analyses were performed using the Kaplan-Meier method and log-rank test. Both univariate and multivariate Cox proportional hazards regression models were applied to analyze independent prognostic factors, and a prognostic nomogram was generated. And the model was validated using the bootstrap method. CONCLUSION Inflammation and nutrition indicators are associated with the prognosis of AGC patients undergoing gastrectomy and prophylactic HIPEC. The nomogram based on the INPI and clinical features supports personalized treatment strategies improving prognosis for AGC patients undergoing gastrectomy and prophylactic HIPEC.