Ensemble machine learning models for predicting bone metastasis in bladder cancer.

ABSTRACT:

Background and purpose

The occurrence of bone metastasis (BM) in advanced bladder cancer (BC) often signifies a poor prognosis. Currently, the accurate prediction of BM in BC remains a challenge. This study develops predictive models using machine learning algorithms to predict bladder cancer bone metastasis (BCBM) and aid in personalized clinical decisions.

Patients and methods

We reviewed and analyzed data from patients diagnosed with BC between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. In addition, we included 327 patients treated at the Second Affiliated Hospital of Nanchang University and Jiangxi Cancer Hospital as an external validation cohort. Independent risk factors for BM in patients with BC were identified through univariate

SUBMITTER: Yu ZJ 

PROVIDER: S-EPMC12509218 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature