Predictive Nomogram and Risk Factors for Lymph Node Metastasis in Bladder Cancer

Area of Science:

• Oncology
• Urology
• Biostatistics

Background:

• Lymph node metastasis (LNM) is a critical prognostic indicator for bladder cancer (BCA).
• Accurate prediction of LNM is essential for determining appropriate treatment strategies for BCA patients.

Purpose of the Study:

• To identify clinicopathological factors associated with LNM in bladder cancer.
• To develop and validate a predictive nomogram for LNM in BCA.
• To analyze the prognostic impact of lymph node status on overall survival in BCA.

Main Methods:

• Utilized Cox proportional hazard and logistic regression models on a large dataset (10,653 patients) from the Surveillance, Epidemiology, and End Results database (2004-2015).
• Developed a nomogram incorporating independent risk factors: T-stage, tumor grade, patient age, and tumor size.
• Validated the nomogram's predictive accuracy using receiver operating characteristic (ROC) curves and calibration plots.

Main Results:

• T-stage, tumor grade, patient age, and tumor size were identified as independent risk factors for LNM.
• The developed LNM nomogram demonstrated effective predictive accuracy in both training (AUC: 0.690) and verification (AUC: 0.704) sets.
• Calibration curves and decision curve analysis confirmed the nomogram's reliability and clinical utility.

Conclusions:

• The novel nomogram accurately and reliably predicts lymph node metastasis in bladder cancer patients.
• This tool can assist clinicians in selecting optimal treatment strategies, potentially improving bladder cancer outcomes.