Construction of differential diagnosis model of benign and malignant breast masses based on ultrasonic breast image reporting and data system with Logistic regression analysis
Construction of differential diagnosis model of benign and malignant breast masses based on ultrasonic breast image reporting and data system with Logistic regression analysis
Objective To construct a differential diagnosis model of benign and malignant breast masses based on breast image reporting and data system(BI-RADS)with Logistic regression analysis and analyze its application value.Method A total of 156 and 67 patients with breast masses were selected as model group and validation group,respective-ly.According to the pathological results,156 patients in model group were divided into benign group(n=87)and malig-nant group(n=69),the clinical features and BI-RADS ultrasound image features of the two groups were recorded,and the influencing factors of malignant breast masses were analyzed by Logistic regression.The differential diagnosis model of benign and malignant breast masses was constructed according to the influencing factors,the receiver operating character-istic(ROC)curve was plotted and the area under the curve(AUC)was calculated to analyze the diagnostic efficiency of the model.Result Univariate analysis showed that there were statistically significant differences in age,maximum mass diameter,lymph node enlargement,BI-RADS classification,ultrasonic elasticity score,orientation,morphology,edge,in-ternal echo,posterior echo,blood supply,structural distortion and micro-calcification between benign group and malig-nant group(P＜0.01).Multivariate Logistic regression analysis showed that age≥40 years,maximum diameter≥3 cm,non-parallel orientation,irregular shape,marginal angulation,marginal burrs,uneven internal echo and micro-calcification were independent risk factors for malignant breast masses(P＜0.05).According to the above eight factors,the differential diagnosis model of benign and malignant breast masses was constructed.The Hosmer-Lemeshow goodness of fit test showed that x2=12.512,P=0.130.The AUC of this model for the diagnosis of malignant breast tumors was 0.896(95％CI:0.844-0.948),the sensitivity was 85.50％,the specificity was 85.10％,and the Youden index was 0.706,indicating that the model had good goodness of fit and diagnostic efficacy.The 67 patients in validation group was included in the diagnos-tic model,the AUC of this model for the diagnosis of malignant breast masses was 0.986(95％CI:0.962-1.000),the sensi-tivity was 93.30％,the specificity was 100％,and the Youden index was 0.933,which showed that the diagnostic efficacy of this model was good.Conclusion The differential diagnosis model of benign and malignant breast masses based on ultrasonic BI-RADS with Logistic regression analysis has high clinical application value,and can be used as an auxiliary means for breast cancer screening.
关键词
乳腺影像报告和数据系统/Logistic回归分析/乳腺肿块/鉴别诊断模型
Key words
breast imaging reporting and data system/Logistic regression analysis/breast mass/differential diagno-sis model
维普
万方数据