Nomograms based on SIRI for predicting postoperative survival outcomes in patients with non-metastatic clear cell...

This study aimed to investigate the prognostic significance of the preoperative Systemic Inflammation Response Index (SIRI) and to develop predictive models for overall survival (OS), cancer specific survival (CSS), and metastasis free survival (MFS) in patients with non-metastatic clear cell renal cell carcinoma (ccRCC) after nephrectomy.

We conducted a retrospective analysis of clinicopathological and prognostic data from 231 non-metastatic ccRCC patients. The optimal cutoff value for SIRI was determined using receiver operating characteristic (ROC) curve analysis. Prognostic factors were identified through least absolute shrinkage and selection operator (LASSO) regression and multivariable Cox proportional hazards models. Nomograms for predicting OS, CSS, and MFS were constructed based on selected predictors. The performance of the nomograms was evaluated using time-dependent ROC curves, time-dependent concordance index (C- index), calibration plots, and decision curve analysis (DCA). The predictive efficacy of our nomograms was compared with that of established models.

Among 231 patients, 21 (9.1%) died including 17 (7.4%) ccRCC-specific deaths; 32 (13.9%) developed postoperative metastases. An elevated SIRI (> 1.405) was independently associated with worse survival outcomes. Multivariable Cox analysis confirmed SIRI as an independent predictor of OS, CSS, and MFS. Nomograms integrating SIRI with other clinicopathological variables were successfully developed. Time dependent ROC curves and C - index demonstrated superior predictive performance of the nomogram compared to conventional clinicopathological characteristics. Calibration plots showed strong agreement between predicted and observed outcomes, and DCA confirmed high clinical utility. Our nomograms outperformed the established Stage, Size, Grade, and Necrosis (SSIGN) score and University of California Los Angeles Integrated Staging System (UISS) models in predictive accuracy.

Elevated pretreatment SIRI independently predicts reduced OS, CSS, and MFS in non-metastatic ccRCC patients. The developed nomograms, which incorporate SIRI and key with clinicopathological characteristics, demonstrate excellent predictive performence, and serve as valuable tools for prognostic assessment in the management of patients with non-metastatic ccRCC.