Development of a prognostic model for elderly patients with metastatic clear cell renal cell carcinoma treated with first-line immuno-oncology combination therapy.

Abstract

BACKGROUND: In the era of immuno-oncology (IO) combination therapy, prognostic tools for elderly patients with metastatic clear cell renal cell carcinoma (ccRCC) are lacking. This study aimed to identify prognostic factors in elderly patients and evaluate a novel risk model using the restricted mean survival time (RMST) and a decision curve analysis (DCA). METHODS: We retrospectively analyzed 203 patients aged ≥70 years with metastatic ccRCC treated with first-line IO combination therapy. Independent prognostic factors for overall survival (OS) were identified. Beyond the hazard ratio, a RMST analysis with a 24-month truncation time quantified absolute survival differences between risk groups. Clinical utility was evaluated using DCA. RESULTS: A multivariable analysis identified low body mass index, low Karnofsky performance status, elevated lactate dehydrogenase, low serum albumin, and liver metastases as independent prognostic factors. In the RMST analysis at 24 months, significant survival disparities were quantified. The intermediate- and poor-risk groups showed mean survival reductions of 1.92 and 6.27 months, respectively, from OS in the favorable-risk group. The model demonstrated a higher net benefit through DCA than the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) classification across a wide range of threshold probabilities for 24-month OS. The model's C-index (0.728) was higher than that of the IMDC classification (0.603). CONCLUSIONS: Our prognostic model for elderly patients provides a practical tool for clinical decision-making by visualizing time-based survival differences via RMST and demonstrating potential clinical utility in DCA.