Construction and external validation of nomogram prediction model for malignant non-mass breast lesions
Objective: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.Methods: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.Results: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.Conclusion: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.
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