The global immune-nutrition-inflammation index (GINI) as a robust prognostic factor in glioblastoma patients treated with the standard stupp protocol

Abstract

Background Systemic inflammation can significantly impact gliomas' onset, progression, and prognosis. Glioblastoma multiforme (GBM) represents the glioma subtype characterized by the most profound inflammatory and immunosuppressive states. Consequently, various blood-borne biomarkers have been scrutinized concerning their prognostic value in GBM patients. Objective We sought to investigate whether the recently introduced Global Immune-Nutrition-Inflammation Index (GINI) holds prognostic significance for GBM patients treated with the standard Stupp protocol. Methods We retrospectively analyzed the data from a cohort of newly diagnosed GBM patients receiving the standard Stupp regimen using the propensity score-matching methodology. The GINI was computed using the original formula: GINI = [(C-reactive protein x Monocytes x Platelets x Neutrophils) divided by (Albumin x Lymphocytes)]. We employed receiver operating characteristic (ROC) curve analysis to identify the optimal cutoff values for GINI, which could help distinguish between different survival outcomes. The primary and secondary objectives were the differences in overall survival (OS) and progression-free survival (PFS) between the GINI groups. Results The optimal GINI cutoff value was 1350. Out of 294 eligible patients, 211 were PSM-matched: GINI<1350 (N = 95) and GINI >= 1350 (N = 116). Comparative Kaplan-Meier estimates indicated that the GINI >= 1350 patients had substantially worse median PFS (8.0 vs 16.8 months;p < .001) and OS (14.3 vs 22.9 months;p < .001) durations than their GINI<1350 counterparts. Conclusion High pretreatment GINI values are robustly and independently associated with inferior PFS and OS outcomes in selected GBM patients who receive standard Stupp protocol. These findings suggest that if further confirmed, the novel GINI could serve as a valuable biological marker for the prognostic stratification of GBM patients.