Related Experiment Video
Updated: May 19, 2026
Establishment and Evaluation of a Risk Prediction Model for Pathological Escalation of Gastric Low-Grade Intraepithelial Neoplasia
Published on: February 16, 2024
A Prognostic Nutritional Scoring System Integrating Inflammatory Markers and Body Composition in Gastric Cancer
Ruiqing Liu1,2, Zhibo Wang3, Jingnong Liu1
1Department of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China, qdu.edu.cn.
Background And Objectives:
Nutrition- and inflammation-related indicators have been shown the prognostic value in cancer patients; however, few studies focus on gastric cancer (GC) patients who underwent prophylactic intraperitoneal hyperthermic chemotherapy (p-HIPEC) following radical gastrectomy. This study is aimed at developing and validating a prognostic nutritional scoring system (PNSS) integrating systemic inflammatory markers and body composition parameters specifically for these patients.
Methods And Results:
Body composition was assessed via computed tomography, and systemic inflammatory markers were recorded preoperatively. A total of 267 patients with GC who received p-HIPEC were included, and the incidences of sarcopenia, myosteatosis, and sarcopenic obesity were 32.6%, 27.3%, and 18.7%, respectively. Logistic regression analysis identified that platelet-to-lymphocyte ratio (PLR) is a significant risk factor for sarcopenia and myosteatosis. The PNSS was constructed using PLR, systemic immune-inflammation index (SII), lymphocyte-to-monocyte ratio (LMR), skeletal muscle index (SMI), and sarcopenia-myosteatosis risk (SMR) score which further integrates skeletal muscle attenuation (MA). This model demonstrated superior predictive accuracy for overall survival (OS) compared to the classic TNM model (C-index: 0.76 vs. 0.71 for 3-year OS in the primary cohort and 0.68 vs. 0.64 for 5-year OS in the validation cohort).
Conclusions:
The PNSS, incorporating both body composition and systemic inflammatory markers, provides robust prognostic value for predicting OS in GC patients undergoing curative resection with p-HIPEC.
