Application Of Gail Model In Breast Ultrasound Classification BI-RADS4 Patient

Objective: Breast cancer is the number one cancer in women with malignant tumors in China,which seriously endangers the physical and mental health of women in China.Using the Gail Breast Cancer Risk Assessment Model,early detection of high-risk breast cancer populations,screening for breast cancer in high-risk populations,recommendations for breast ultrasound findings and BI-RADS classification into four types of patients for biopsy,and early improvement Diagnostic accuracy and treatment efficiency,reducing patient suffering,has important clinical significance.Methods: 461 patients who underwent breast Ultrasound in the Department of Gastrointestinal Surgery of First Affiliated Hospital of Guangxi Medical University from January 2018 to December 2018,and who were diagnosed as BI-RADS 4 and experience Mammon biopsyin our hospital.Collect Gail model related indicators:Age,menarche,primitive age,number of breast biopsies and history of breast disease,first-degree family history,ethnicity,and pathological diagnosis,calculate 5 years of risk and lifetime risk.Calculating the 5-year risk accuracy rate by calculating the Gail model with pathological results as the gold standard;Draw the receiver operating characteristic curve,calculate the area under the curve,sensitivity,specificity,and redefine the optimal cut-off pointaccording to the most Youden index.The cut-off points were divided into high-risk group and low-risk group,and the prediction accuracy of the two groups in BI-RADS4,4a,4b,and 4c patients was compared.The results were analyzed by SPSS22.0,with P<0.05 as the significance test level.Results: The Gail model has a lower accuracy of 5-year risk in BI-RADS4 patients with a threshold of 1.67%;The ROC curve was drawn and the optimal cut-off value was 0.8%.The age,menarche age,primitive age,the number of biopsy,and the number of first-degree family members were different between high-risk and low-risk groups.The positive rate in patients with BI-RADS4 was59.3% in the high-risk group and 34.5% in the low-risk group,P=0.000;positive rate in 4b class: 37.1% in high risk group,15.6% in low risk group,P=0.001;positive rate in 4b class: 58.5% in high risk group,38.5% in low risk group,P=0.032;positive rate of 4c class: high risk group 72.8%,low risk group 78.3%,P=0.474.Conclusion: The Gail model has a low prediction accuracy in BI-RADS 4patients with >1.67% high risk;With a threshold of 0.8%,the Gail model has predictive value for the occurrence of breast cancer in patients with ultrasound BI-RADS4:In the 4a and 4b patients,the high-risk group had a significantly higher positive rate for breast cancer diagnosis than the low-risk group.In the BI-RADS 4c patients,the positive and negative rates of breast cancer diagnosis in the high-risk group of the Gail breast cancer risk assessment model were significantly similar to those in the low-risk group,indicating that the Gail breast cancer risk assessment model for ultrasound BI-RADS4 a,4b The occurrence of breast cancer in patients with type has predictive value.