Nomograms to predict individual prognosis of patients with squamous cell carcinoma of the urinary bladder.

On the basis of some significant clinical parameters, we had an intent to establish nomograms for estimating the prognosis of patients with squamous cell carcinoma of the urinary bladder (SCCB), including overall survival (OS) and cancer-specific survival (CSS).

The data of 1210 patients diagnosed with SCCB between 2004 and 2014,were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The Cox proportional hazards regression model was applied to evaluate the association between variables and survival. Nomograms were constructed to predict the OS and CSS of an individual patient based on the Cox model. In the end, the performance of nomograms was internally validated by using calibration curves, concordance index (C-index), and k-fold cross-validation.

Several common indicators were taken into the two nomograms (OS and CSS), including age at diagnosis, marital status, sex, TNM stage, surgical approach, tumor size, and lymph node ratio while the OS nomogram additionally contained race, grade, and chemotherapy. They had an excellent predictive accuracy on 1- and 3- year OS and CSS with C-index of 0.733 (95% confidence interval [CI], 0.717-0.749) for OS and 0.724 (95% CI, 0.707-0.741) for CSS. All calibration curves showed great consistency between actual survival and predictive survival.

The nomograms with improved accuracy and applicability on predicting the survival outcome of patients with SCCB would provide a reliable tool to help clinicians to evaluate the risk of patients and make individual treatment strategies.

BMC cancer. 2019 Dec 09*** epublish ***

Guanghao Zhang, Zhiwei Li, Daoqing Song, Zhiqing Fang

Department of Urology, Qilu Hospital of Shandong University, No. 107 West Wenhua Road, Jinan, Shandong Province, China., Department of Neurosurgery, Qilu Hospital of Shandong University, Jinan, Shandong Province, China., Department of Urology, Qilu Hospital of Shandong University, No. 107 West Wenhua Road, Jinan, Shandong Province, China. .