Machine learning predicts the prognosis of breast cancer patients with initial bone metastases.

ABSTRACT:

Background

Bone is the most common metastatic site of patients with advanced breast cancer and the survival time is their primary concern; however, we lack accurate predictive models in clinical practice. In addition to this, primary surgery for breast cancer patients with bone metastases is still controversial.

Method

The data used for analysis in this study were obtained from the SEER database (2010-2019). We made a COX regression analysis to identify prognostic factors of patients with bone metastatic breast cancer (BMBC). Through cross-validation, we constructed an XGBoost model to predicting survival in patients with BMBC. We also investigated the prognosis of patients treated with neoadjuvant chemotherapy plus surgical and chemotherapy alone using propensity score matc

SUBMITTER: Li C 

PROVIDER: S-EPMC9549149 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature