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Updated: Nov 4, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Bone Metastasis in Renal Cell Carcinoma Patients: Risk and Prognostic Factors and Nomograms
Zhiyi Fan1,2, Zhangheng Huang2, Xiaohui Huang1
1Hangzhou Medical College, Hangzhou, Zhejiang Province, China.
Background:
Bone metastasis (BM) is one of the common sites of renal cell carcinoma (RCC), and patients with BM have a poorer prognosis. We aimed to develop two nomograms to quantify the risk of BM and predict the prognosis of RCC patients with BM.
Methods:
We reviewed patients with diagnosed RCC with BM in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Multivariate logistic regression analysis was used to determine independent factors to predict BM in RCC patients. Univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors for BM in RCC patients. Two nomograms were established and evaluated by calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).
Results:
The study included 37,554 patients diagnosed with RCC in the SEER database, 537 of whom were BM patients. BM's risk factors included sex, tumor size, liver metastasis, lung metastasis, brain metastasis, N stage, T stage, histologic type, and grade in RCC patients. Currently, independent prognostic factors for RCC with BM included grade, histologic type, N stage, surgery, brain metastasis, and lung metastasis. The calibration curve, ROC curve, and DCA showed good performance for diagnostic and prognostic nomograms.
Conclusions:
Nomograms were established to predict the risk of BM in RCC and the prognosis of RCC with BM, separately. These nomograms strengthen each patient's prognosis-based decision making, which is critical in improving the prognosis of patients.
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