Abstract
Background
Papillary RCC (PRCC) is the second most common pathological subtype after clear cell RCC (ccRCC), representing 10–20% of treatment of renal tumors. The aim of this study was to establish a reliable nomogram model to evaluate the prognosis of papillary renal cell carcinoma (PRCC) for overall survival (OS).
Patients and methods
: In total, 6,028 patients with PRCC from the Surveillance, Epidemiology, and End Results (SEER) database were randomly separated into training (n = 4,220) and validation (n = 1,808) cohorts. Cox regression analyses were used to identify the significant variables. A nomogram was established to predict the prognosis of an individual patient with PRCC in terms of OS based on the Cox model. The predictive accuracy of the nomogram model was assessed via discrimination and calibration plots.
Results
Data of 6,028 patients with PRCC were retrieved from the SEER database. Age at diagnosis, grade, Tumor-Node-Metastasis stage (TNM, AJCC, 7th edition), surgical treatment, tumor number and marital status were the significant independent prognostic variables. All variables were combined to establish a nomogram. Compared to the TNM stage system 7th edition, our nomogram exhibited a favorable discrimination power for OS prediction both in the training and validation cohorts. The calibration curves revealed high consistency between the prognosis prediction of our nomogram and the actual survival.
Conclusions
The nomogram displayed a excellent performance, suggesting that it could be considered an effective and individualized tool for prognosis prediction of OS in patients with PRCC.
A Novel Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Patients with Papillary Renal Cell Carcinoma
