Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Occult Breast Cancer Patients.

ABSTRACT:

Background

Occult breast cancer (OBC) is an uncommon malignant tumor and the prognosis and treatment of OBC remain controversial. Currently, there exists no accurate prognostic clinical model for OBC, and the treatment outcomes of chemotherapy and surgery in its different molecular subtypes are still unknown.

Methods

The SEER database provided the data used for this study's analysis (2010-2019). To identify the prognostic variables for patients with ODC, we conducted Cox regression analysis and constructed prognostic models using six machine learning algorithms to predict overall survival (OS) of OBC patients. A series of validation methods, including calibration curve and area under the curve (AUC value) of receiver operating characteristic curve (ROC) were employed to vali

SUBMITTER: Qu J 

PROVIDER: S-EPMC10179501 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature