ArticleJournal of hepatocellular carcinoma2026
Prognostic Nomogram for Hepatocellular Carcinoma Patients with High Systemic Immune-Inflammation Index: Validation in Surgical and Immunotherapy Cohorts and Exploration of Immune Microenvironment Mechanisms.
Article in Journal of hepatocellular carcinoma, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The systemic immune-inflammation index (SII) has emerged as a robust prognostic indicator in hepatocellular carcinoma (HCC). However, precise risk stratification for HCC patients with high preoperative inflammatory burden-a group typically associated with poor prognosis-remains a clinical challenge. This study aimed to develop and validate a multi-center radiomics-clinicopathologic nomogram to optimize individualized survival prediction for this specific subpopulation. Methods: We conducted a multi-center retrospective study involving HCC patients with high preoperative SII from two medical centers. Patients were stratified into a training cohort, an external validation cohort, and an independent immunotherapy cohort to evaluate model generalizability. Radiomics features were extracted from preoperative imaging. A prognostic nomogram was constructed using multivariable Cox regression analysis, integrating the radiomics score (Rad-score), clinical factors (e.g. tumor diameter, AFP), and pathologic features. The model's performance was rigorously assessed via C-index, calibration curves, and Decision Curve Analysis (DCA). Furthermore, bulk transcriptomic analysis of our own patient samples was performed to elucidate the underlying immune microenvironment mechanisms associated with high SII. Results: The integrative nomogram demonstrated superior predictive accuracy compared to traditional staging systems. In the training cohort, the C-index was 0.796, which remained robust in the external surgical validation cohort (0.775). DCA confirmed that the nomogram provided significant clinical net benefit across different therapeutic settings. Transcriptomic analysis revealed that high-risk patients were characterized by an immunosuppressive microenvironment, marked by the enrichment of pathways related to cytokine-cytokine receptor interaction and significant infiltration of regulatory T cells (Tregs). Conclusion: We developed and validated a robust radiomics-clinicopathologic nomogram specifically for HCC patients with high inflammatory burden. This multi-center tool provides accurate risk stratification across both surgical and immunotherapy settings, potentially facilitating more personalized clinical decision-making.
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