ArticleFrontiers in nutrition2025
The global immune-nutrition-inflammation index predicts pathological response and survival in esophageal squamous cell carcinoma treated with neoadjuvant immunochemotherapy.
Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- The Global Immune-Nutrition-Inflammation Index (GINI) in Acute Pancreatitis Severity Assessment: A Comparative Study.Digestive diseases and sciences · 2026Article
- Article
- The Global Immune-Nutrition-Inflammation Index Is Associated with Survival Outcomes and Enhances Prognostic Discrimination in Metastatic Pancreatic Cancer.Medicina (Kaunas, Lithuania) · 2026Article
- Association of the global inflammatory-nutritional index (GINI) with time to next treatment and overall survival in patients with metastatic colorectal cancer receiving third-line therapy: a real-world retrospective study.Journal of gastrointestinal oncology · 2026Article
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Abstract
Objective: The global immune-nutrition-inflammation index (GINI) is a new composite indicator that assesses nutrition and inflammation and has been linked to prognosis in various cancers. Neoadjuvant immunochemotherapy (nICT) is becoming more common for treating locally advanced esophageal squamous cell carcinoma (ESCC). However, the potential of GINI to predict outcomes for ESCC patients undergoing nICT has not yet been explored. This study aims to examine the predictive value of the pretreatment GINI in relation to pathological response and prognosis for ESCC patients receiving nICT. Methods: A total of 138 patients with locally advanced ESCC who underwent nICT followed by radical resection at our institution between 2022 and 2024 were retrospectively included in this study. The GINI index was calculated from pretreatment blood parameters. The receiver operating characteristic (ROC) curve analysis was conducted to determine the optimal cutoff value of the GINI index for predicting pathological response, which was defined using the Becker tumor regression grade (TRG). Logistic regression and Cox proportional hazards models were used to analyze the associations between the GINI index and both pathological response and survival outcomes. Results: The optimal cutoff value of GINI for predicting pathological response was 73.47 (AUC = 0.912). Multivariate analysis identified high-GINI as an independent risk factor for both poor pathological response (OR = 1.05, Conclusion: Pretreatment GINI is a promising biomarker for predicting pathological response and survival outcomes in locally advanced ESCC patients treated with nICT. A high GINI level is significantly associated with treatment resistance and poorer prognosis, suggesting its potential utility in risk stratification and guiding individualized treatment strategies.
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