Artificial neural network models to predict nodal status in clinically node-negative breast cancer.

ABSTRACT:

Background

Sentinel lymph node biopsy (SLNB) is standard staging procedure for nodal status in breast cancer, but lacks therapeutic benefit for patients with benign sentinel nodes. For patients with positive sentinel nodes, individualized surgical strategies are applied depending on the extent of nodal involvement. Preoperative prediction of nodal status is thus important for individualizing axillary surgery avoiding unnecessary surgery. We aimed to predict nodal status in clinically node-negative breast cancer and identify candidates for SLNB omission by including patient-related and pathological characteristics into artificial neural network (ANN) models.

Methods

Patients with primary breast cancer were consecutively included between January 1, 2009 and December 31, 2012 i

SUBMITTER: Dihge L 

PROVIDER: S-EPMC6588854 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature