Construction and validation of a risk prediction model for clinical axillary lymph node metastasis in T1-2 breast cancer.

ABSTRACT: The current diagnostic technologies for assessing the axillary lymph node metastasis (ALNM) status accurately in breast cancer (BC) remain unsatisfactory. Here, we developed a diagnostic model for evaluating the ALNM status using a combination of mRNAs and the T stage of the primary tumor as a novel biomarker. We collected relevant information on T1-2 BC from public databases. An ALNM prediction model was developed by logistic regression based on the screened signatures and then internally and externally validated. Calibration curves and the area under the curve (AUC) were employed as performance metrics. The prognostic value and tumor immune infiltration of the model were also determined. An optimal diagnostic model was created using a combination of 11 mRNAs and T stage of the primary tu

SUBMITTER: Luo N 

PROVIDER: S-EPMC8758717 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature