The Nutritional Risk Index as a Biomarker of Host-Tumor Interaction in HBV-Related Hepatocellular Carcinoma: From Clinical Observation to Genomic Validation

Objective This study aimed to evaluate the prognostic value of the Nutritional Risk Index (NRI) and Prognostic Nutritional Index (PNI) in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after curative resection. We further sought to elucidate the underlying genomic rationale linking NRI to tumor biology. Methods A retrospective cohort of 146 HBV-related HCC patients who underwent curative hepatectomy was analyzed. Propensity score matching (PSM) was performed to validate the robustness of NRI. Integrated bioinformatics analysis of the TCGA-LIHC cohort was conducted to explore the association between albumin (ALB) expression—the core component of NRI—and HCC driver gene mutations. An NRI-based nomogram was constructed for individualized survival prediction. Results NRI, but not PNI, was identified as an independent prognostic factor for both overall survival (OS) and recurrence-free survival (RFS). After 1:1 PSM, a high NRI (≥ 102.06) remained significantly associated with improved OS (P = 0.0293). Stratified analysis revealed that the prognostic power of NRI was most pronounced in early-stage (TNM Ⅰ+Ⅱ) and non-vascular invasion subgroups. Integrated analysis of TCGA data demonstrated that low ALB expression was robustly associated with TP53 and CTNNB1 mutations (P < 0.05), suggesting a link between NRI and genomic instability. The NRI-based nomogram, incorporating TNM stage, PIVKA-II, and vascular invasion, exhibited favorable discriminative ability (C-index: 0.78) and clinical utility. Conclusion NRI is a reliable and cost-effective prognostic indicator for HBV-related HCC, particularly in early-stage disease. Our findings reveal a "non-nutritional" face of NRI, suggesting that it serves as a serological signature of high-risk molecular subtypes characterized by genomic instability. The NRI-based nomogram provides a practical tool for risk stratification and clinical decision-making.