Logistic regression model in evaluation on diagnosis of breast nodules classification of breast imaging reporting and data system 3-5 category with automated breast volume scanner combined with conventional ultrasound
10.13929/j.1672-8475.201710027
- VernacularTitle:Logistic回归模型评价自动乳腺全容积扫描联合常规超声诊断乳腺影像报告及数据系统3～5类结节
- Author:
Jingmin LI
1
;
Yuhong SHAO
;
Xiuming SUN
;
Hui ZHANG
;
Peng LI
;
Bin WANG
Author Information
1. 北京大学第一医院超声科
- Keywords:
Ultrasonography;
Breast neoplasms;
Logistic regression
- From:
Chinese Journal of Interventional Imaging and Therapy
2018;15(5):282-285
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of Logistic regression model in evaluation on automated breast volume scanner (ABVS) combined with conventional ultrasound in differential diagnosis of breast imaging reporting and data system(BI-RADS) 3-5 category breast nodules.Methods Totally 216 patients (247 BI-RADS 3-5 category breast nodules) underwent ABVS and conventional ultrasound.Taking puncture biopsy or postoperative pathology as the gold standards,Logistic regression model was established and main ultrasound characteristics in diagnosis of breast malignant nodules of BI-RADS 3 5 category were screened and evaluated.Finally,ROC curve of evaluating the diagnostic efficiency of Logistic regression model was drawn.Results There were 4 independent variables in diagnosis of breast malignant nodules of BI-RADS 3 5 category,including " Retraction phenomenon" (X1,odds ratio [OR] =12.03,P＜ 0.01)," microlobulated margin" (X2,OR-6.00,P＜0.01),border (X6,OR=11.48,P=0.01) and anteroposterior to transverse ratio (A/T,X8,OR=4.09,P=0.01).OR of "retraction phenomenon" was the highest.The regression equation was Logit(P) =-4.43+2.49X1 + 1.79X2 +2.44X6 +1.41X8 (x2 =196.32,P＜0.01),and the area under the ROC curve was 0.95 (P＜ 0.01).Conclusion Logistic regression model has great value in differential diagnosis of breast malignant nodules of BI-RADS 3-5 category.
