Nomogram for predicting long-term survival in renal cell carcinoma patients undergoing thermal ablation

Thermal Ablation (TA) represents a valid option for management of renal cortical neoplasms. Recognizing paucity of tools to predict overall survival (OS) for patients undergoing TA, we developed a nomogram to offer personalized OS predictions utilizing the National Cancer Database.

We included patients diagnosed with primary renal tumors who underwent TA between 2004 and 2020. Cox proportional hazards (CPH) model included age, Charlson-Deyo Comorbidity Index (CCI), tumor size, insurance status, ethnicity, histology, and tumor grade. A nomogram was developed to predict OS at 1, 5, and 10 years using a multivariable CPH model. Model robustness was confirmed through bootstrap validation with 1,000 iterations. Model performance was evaluated using Harrell's C-index, calibration plots at 1, 5, and 10 years, and time-dependent area under the curve (AUC) from ROC curves for 1-, 5-, and 10-year OS predictions RESULTS: We identified 10,121 patients (median age: 69 years; median follow-up: 55 months). Significant predictors of worse OS included advanced age (Hazard Ratio [HR] = 1.04, P < 0.001), higher CCI (HR = 2.20, P < 0.001), larger tumor size (HR = 1.03, P < 0.001), non-private insurance (HR = 2.16, P < 0.001), high-grade (HR = 1.31, P < 0.001), and clear cell (HR = 1.14, P = 0.015). Bootstrap validation confirmed the stability of the model, which achieved a C-index of 0.68. Calibration plots showed agreement between predicted and observed survival probabilities at 1, 5, and 10 years, with AUC values of 0.70, 0.71, and 0.74, respectively.

We constructed a nomogram incorporating clinical, pathological, and socioeconomic factors to offer personalized OS prediction for TA. Future research should focus on external validation and clinical implementation.