Factors influencing the performance of a diagnostic model including contrast-enhanced ultrasound in 1023 breast lesions: comparison with histopathology
Author(s) -
Yijie Chen,
Lina Tang,
Zhongshi Du,
Zhaoming Zhong,
Jun Luo,
Lichun Yang,
Ruoxia Shen,
Yan Cheng,
Zizhen Zhang,
Ehui Han,
Zhihong Lv,
Lijun Yuan,
Yong Yang,
Yinrong Cheng,
Lei Yang,
Shengli Wang,
Baoyan Bai,
Qin Chen
Publication year - 2019
Publication title -
annals of translational medicine
Language(s) - English
Resource type - Journals
eISSN - 2305-5847
pISSN - 2305-5839
DOI - 10.21037/atm.2019.10.83
Subject(s) - lesion , medicine , logistic regression , histopathology , contrast enhanced ultrasound , radiology , ultrasound , univariate analysis , univariate , pathological , multivariate analysis , pathology , multivariate statistics , statistics , mathematics
BackgroundWe aimed to investigate the influence of patient and lesion characteristics on our diagnostic model for contrast-enhanced ultrasound (CEUS) of the breast, comparing its accuracy with that of histopathology.MethodsConducting a study with eight medical centers, we compared 1,023 breast lesions categorized as BI-RADS 4 or 5 with the score from our newly-established CEUS-based diagnostic model, comparing the results with pathological outcomes. Univariate and multivariate logistic regression analyses were conducted to determine the influence of clinicopathological characteristics on the performance of this CEUS model.ResultsLogistic regression analysis showed that patients' age, maximum lesion diameter, and distance from the lesion's deep edge to the pectoralis major were significant independent influencing factors. The model's diagnostic accuracy was greater for patients >35 y (P=0.005), for maximum lesion diameter >20 mm, and for distance from the lesion's deep edge to the pectoralis major ≤3.05 mm. There was no significant difference in accuracy between lesions with maximum lesion diameter 10-20 and <10 mm (P=0.393).ConclusionsThe diagnostic performance of the proposed CEUS model for breast lesions is influenced by patients' age, maximum lesion diameter, and distance from the lesion's deep edge to the pectoralis major. Consideration of influencing factors is required to optimize clinical use of the CEUS model.
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