A nomogram predicting the OS and CSS of ≥ T1b renal cell carcinoma patients after surgery

The aim of this study was to develop and validate a nomogram for predicting the overall survival (OS) and cancer-specific survival (CSS) of renal cell carcinoma (RCC) patients after surgery.

From 2010 to 2021, clinical data of ≥ T1b RCC patients underwent surgical intervention were retrieved from Surveillance, Epidemiology, and End Results (SEER) database. All enrolled patients were randomly allocated to a training set and a validation set. Variables were screened using Least absolute shrinkage and selection operator (LASSO) regression and Cox regression was employed to develop nomograms. The accuracy of these nomograms was evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

A total of 4,429 patients were included in this study, with 3,101 and 1,328 patients in the training and validation set, respectively. Multivariate analysis indicated that Grade, Tumor size, Tumor (T), Node (N), Metastasis (M) stage, and Radiation were common independent prognostic factors for OS and CSS in RCC patients. The C-index and ROC curves demonstrated that the two nomograms for OS and CSS had favorable discrimination and calibration ability. DCA indicated that the nomograms achieved more clinical net benefits than the American Joint Committee on Cancer (AJCC) staging system. Additionally, patients were divided into high-risk and low-risk groups based on the nomogram scores. The Kaplan-Meier curves demonstrated significant differences in OS and CSS between the two groups.

We developed and validated two effective prognostic nomograms designed to predict 1-, 3-, and 5-year OS and CSS rates for ≥ T1b RCC patients, which can serve as an important supplement to the present predictive models.