To analyze the ultrasound features of non-mass lesions (NMLs) of the breast by logistic regression, to establish a predictive model for the malignancy risk of NMLs in nomogram, and to improve the diagnostic ability of sonographers for NMLs.

The ultrasound image features of 493 cases of NMLs from 488 people in Xijing Hospital were retrospectively analyzed and divided into a training set and an internal validation set in a ratio of 7:3, and an independent external validation set of 72 cases from Taizhou Hospital in Zhejiang Province. The malignant risk factors of NMLs were screened out, a nomogram prediction model was constructed, and the model was evaluated using ROC and calibration curves.

Multifactorial analysis showed that calcification, structural distortion, age, and size were independent risk factors for malignancy in NMLs (P<0.05). The training set, internal validation set, and external validation set AUCs of the nomogram prediction model were 0.91, 0.89, and 0.94, respectively, with sensitivities of 86%, 86%, and 95%, and specificities of 80%, 77%, and 87%. The calibration curves of the model showed good agreement, with mean absolute errors of 0.014, 0.034, and 0.058, respectively.

The malignant risk nomogram prediction model constructed based on the independent risk factors mentioned above has a reliable clinical reference value, and it can assist sonographers in improving their diagnostic ability for NMLs.