A composite immune-nutritional and tumor marker score predicts outcomes in LA-ESCC treated with neoadjuvant...

Neoadjuvant chemoimmunotherapy (nCIT) has improved outcomes in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC). However, accessible and reliable biomarkers to predict survival and pathological response remain limited. This study assessed the prognostic and predictive value of the Global Immune-Nutrition Index (GINI), cytokeratin-19 fragment (CYFRA 21 - 1), fibrinogen-albumin ratio index (FARI), and a composite score combining these markers-the GINI-CYFRA 21 - 1-FARI (GCF) score.

A retrospective analysis was conducted on 138 LA-ESCC patients who received nCIT followed by radical esophagectomy between 2021 and 2023. Optimal cut-off values for GINI, CYFRA 21 - 1, and FARI were determined using X-tile software. The composite GCF score was developed accordingly. Associations with disease-free survival (DFS) were evaluated using Kaplan-Meier analysis and multivariable Cox regression. Predictive performance was assessed via time-dependent ROC curves. Tumor regression grade (TRG) was analyzed using logistic regression, and a nomogram was constructed to predict pathological response.

Elevated levels of GINI (median DFS: 20 vs. not estimable [NE] months; p = 0.001), CYFRA 21 - 1 (19 vs. NE months; p < 0.001), FARI (11 vs. 26 months; p < 0.001), and higher GCF scores (0 vs. 1 vs. ≥2: 18 vs. 22 vs. NE months; p < 0.001) were associated with worse DFS. The GCF score was independently predictive of DFS (low vs. high: HR = 0.264; p = 0.028) and demonstrated consistent discriminative capacity. For pathological response, the GCF score showed predictive value for TRG (AUC = 0.625; p = 0.004) and was independently associated with poor TRG (high vs. low: OR = 2.170; p = 0.048). A nomogram incorporating the GCF score outperformed models excluding it (AUC: 0.787 vs. 0.662; p < 0.05).

The GCF score-a composite of GINI, CYFRA 21 - 1, and FARI-independently predicts DFS and pathological response following nCIT and surgery in LA-ESCC, and may hold potential as a practical, blood-based biomarker. Its integration significantly enhances predictive model performance and may aid in individualized patient risk stratification.