A nomogram for predicting node-positive disease in muscle-invasive bladder cancer

Background: Non-metastatic muscle-invasive bladder cancer (MIBC) with lymph node (LN) metastasis is an aggressive disease with a poor prognosis. This study aimed to investigate risk factors for node-positive disease (pN+) and develop a nomogram to predict the likelihood of LN metastases in MIBC patients using a large population-based cancer database. Methods: : Data of all patients with non-metastatic MIBC from 2004 to 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and analyzed retrospectively. Logistic regression analyses were used to identify independent risk factors of pN+ to develop nomogram. Predictive nomogram was carried out with R software to identify the LN involvement. The performance of the nomogram model was evaluated by calibration slope and receiving operating characteristic (ROC) curve. Results: : A total of 12,269 non-metastatic MIBC patients in the SEER database were included. Larger tumor size, overlapping lesion, young age, female, poorly differentiated histological grade, and advanced T stage, are independent risk factors for pN+. We integrated the above variables into the models. The area under the curve (AUC) of ROC curve was 0.704. We separated non-metastatic MIBC patients into three groups according to the risk classification system of the likelihood of LN metastases, in which intermediate or high risk for LN metastases might not be good candidates for bladder preservation. Conclusions: : We performed the first accurate nomogram with clinical and oncological variables for LN involvement of non-metastatic MIBC patients, which might help clinicians in patient risk stratification and outcome estimation.