A Bayesian network predicting survival of cervical cancer patients-Based on surveillance, epidemiology, and end results.

ABSTRACT: This study aimed to build a comprehensive model for predicting the overall survival (OS) of cervical cancer patients who received standard treatments and to build a series of new stages based on the International Federation of Gynecologists and Obstetricians (FIGO) stages for better such predictions. We collected the cervical cancer patients diagnosed since the year 2000 from the Surveillance, Epidemiology, and End Results (SEER) database. Cervical cancer patients who received radiotherapy or surgery were included. Log-rank tests and Cox regression were used to identify potential factors of OS. Bayesian networks (BNs) were built to predict 3- and 5-year survival. We also grouped the patients into new stages by clustering their 5-year survival probabilities based on FIGO stage, age, and tum

SUBMITTER: Liu G 

PROVIDER: S-EPMC9986069 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature