Development and Validation of a Nomogram for Predicting Breast Malignancy in Male Patients Based on Clinical and Ultrasound Features.

Abstract

This study aimed to construct a nomogram based on clinical and ultrasound (US) features to predict breast malignancy in males. The medical records between August, 2021 and February, 2023 were retrospectively collected from the database. Patients included in this study were randomly divided into training and validation sets in a 7:3 ratio. The models for predicting the risk of malignancy in male patients with breast lesions were virtualized by the nomograms. Among the 71 enrolled patients, 50 were grouped into the training set, while 21 were grouped into the validation set. After the multivariate analysis was done, pain, BI-RADS category, and elastography score were identified as the predictors for malignancy risk and were selected to generate the nomogram. The C-index was 0.931 for the model. Concordance between predictions and observations was detected by calibration curves and was found to be good in this study. The model achieved a net benefit across all threshold probabilities, which was shown by the decision curve analysis (DCA) curve. We successfully constructed a nomogram to evaluate the risk of breast malignancy in males using clinical and US features, including pain, BI-RADS category, and elastography score, which yielded good predictive performance.