Objective::
This study aimed to construct a nomogram based on clinical and ultrasound
(US) features to predict breast malignancy in males.
Methods::
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
Results::
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.
Conclusion::
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.