Prognostic value of systemic immune-inflammation index in patients with localized and advanced renal cell carcinoma: a systematic review and meta-analysis.

BACKGROUND: Although several individual studies have suggested its potential role, comprehensive evidence across the overall renal cell carcinoma (RCC) population remains lacking. This study aimed to systematically assess the prognostic value of the systemic immune-inflammation index (SII) among patients diagnosed with RCC. METHODS: A structured literature search was performed across PubMed, Embase, Web of Science, and the Cochrane Library to retrieve eligible studies published up to October 2025. These studies examined the association between SII and clinical outcomes such as overall survival (OS), progression-free survival (PFS), or cancer-specific survival (CSS) in patients with RCC. To synthesize the data, pooled hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) were calculated using a random-effects model. Additionally, the consistency of the outcomes and potential heterogeneity across studies were examined using subgroup and sensitivity analyses. RESULTS: A total of 22 individual studies fulfilled the criteria for inclusion in the analysis. The meta-analysis demonstrated that higher SII was significantly associated with worse OS (HR =1.89, 95% CI: 1.64-2.18, P<0.001), PFS (HR =1.74, 95% CI: 1.53-1.97, P<0.001), and CSS (HR =1.63, 95% CI: 1.01-2.63, P=0.04). Subgroup analyses indicated that these associations were consistent across different subgroups and suggested that geographic region, SII cut-off values, and disease stage were the main sources of heterogeneity. The results remained consistent across sensitivity analyses, supporting their reliability. CONCLUSIONS: This study demonstrates that SII is a strong, independent prognostic predictor for patients with RCC, with prognostic relevance across the disease course and practical accessibility in clinical practice. Future prospective studies are warranted to establish standardized cut-off values and further elucidate the underlying biological mechanisms.