Radical surgery is effective for localized Renal Cell Carcinoma (RCC). However, recurrence occurs in up to 40% of patients, underscoring the need for adjuvant therapy to improve the prognosis. Historically, adjuvant treatments, including tyrosine kinase inhibitors, have shown limited success, failing to improve overall survival. The introduction of the immune checkpoint inhibitor pembrolizumab, as demonstrated in the KEYNOTE-564 trial, has revolutionized the field by showing significant overall survival benefits and prompting updates to RCC treatment guidelines. Accurate risk assessment is critical for identifying high-risk patients most likely to benefit from adjuvant therapy. Established risk models, such as the UCLA Integrated Staging System and the Leibovich score, incorporate clinical and pathological factors to stratify recurrence risk. Recent enhancements in these models have improved predictive accuracy, enabling better optimization of inclusion criteria for clinical trials targeting high-risk recurrence and the development of individualized surveillance protocols to refine patient selection for adjuvant treatment. This review examines the evolution of risk stratification models and adjuvant therapy for RCC, highlighting the potential of innovative biomarkers, such as liquid biopsies, to further enhance patient selection and optimize treatment outcomes. Ongoing clinical trials investigating new combinations of immune checkpoint inhibitors hold promise, and integrating accurate risk assessment with advanced immunotherapy will be key to improving postoperative survival rates for patients with RCC.
