Clinical Risk Models, Inflammatory–Nutritional Indices and a Neural-Network Survival Model in Metastatic Renal Cell Carcinoma: A Single-Center Retrospective Study

Background/Objectives: In metastatic renal cell carcinoma (mRCC), the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) and Memorial Sloan Kettering Cancer Center (MSKCC) risk models remain the primary tools for prognostic stratification but may not fully capture outcome heterogeneity in the contemporary treatment era. Systemic inflammatory–nutritional biomarkers such as the pan-immune-inflammation value (PIV) and the hemoglobin–albumin–lymphocyte–platelet (HALP) score have emerged as complementary, readily available prognostic indicators, yet their added value alongside established risk models, nephrectomy status, and modern predictive approaches such as machine learning remains poorly defined in real-world cohorts. This study jointly evaluated established risk models, inflammatory–nutritional biomarkers, and an exploratory neural-network survival model for prognostication in mRCC.