A Simple-To-Use Nomogram for Predicting Early Death in Metastatic Renal Cell Carcinoma: A Population-Based Study

BackgroundMetastatic renal cell carcinoma (mRCC) is usually considered to have a poor prognosis, which has a high risk of early death (<= 3 months). Our aim was to developed a predictive nomogram for early death of mRCC. MethodsThe SEER database was accessed to obtain the related information of 6,005 mRCC patients between 2010 and 2015. They were randomly divided into primary cohort and validation cohort in radio of 7:3. The optimal cut-off point regarding age at diagnosis and tumor size were identified by the X-tile analysis. Univariate and multivariate logistic regression models were applied to determine significant independent risk factors contributed to early death. A practical nomogram was constructed and then verified by using calibration plots, receiver operating characteristics (ROCs) curve, and decision curve analysis (DCA). ResultsThere were 6,005 patients with mRCC included in the predictive model, where 1,816 patients went through early death (death within <= 3 months of diagnosis), and among them 1,687 patients died of mRCC. Based on 11 significant risk factors, including age, grade, N-stage, histologic type, metastatic sites (bone, lung, liver and brain) and treatments (surgery, radiation, and chemotherapy), a practical nomogram was developed. The model's excellent effectiveness, discrimination and clinical practicality were proved by the AUC value, calibration plots and DCA, respectively. ConclusionsThe nomogram may play a major part in distinguishing the early death of mRCC patients, which can assist clinicians in individualized medicine.