Nomograms for predicting survival in patients with micropapillary bladder cancer: a real-world analysis based on the surveillance, epidemiology, and end results database and external validation in a tertiary center

Background The present study aimed to construct and validate nomograms that can be used to predict cancer-specific survival (CSS) and overall survival (OS) in patients with micropapillary bladder cancer. Methods The data of 627 patients diagnosed with micropapillary bladder cancer between 2000 and 2018 were obtained from the surveillance, epidemiology, and end results database. Patients were randomly divided into the training and internal validation sets (7:3). The Cox proportional hazards regression model was applied to evaluate the association between variables and survival and then nomograms were constructed to predict the survival of an individual patient. The performance of nomograms was validated by using calibration curves, concordance index, receiver operating characteristic curves with the calculated area under the curve and decision curve analysis in the training and internal validation set. Data from 41 micropapillary bladder cancer patients at Qilu Hospital of Shandong University from 2000 to 2022 were collected for external validation. Results Several independent risk factors were taken into the two nomograms (CSS and OS), including age, marital status, AJCC TMN stage, surgical approach, lymph node ratio, and tumor size while the OS nomogram additionally contained race. The concordance index of the training set, internal validation set, and external verification set were all over 0.7. The calibration curve indicated good consistence between the nomogram prediction and actual survival. Area under the curve and decision curve analysis results indicated great clinical usefulness of nomograms. Conclusions The nomograms predicting the survival outcome of patients with micropapillary bladder cancer would provide a valuable tool to help clinicians to evaluate the risk of patients and make individual treatment strategies.