| Objective: The Gail Breast Cancer Risk Prediction Model(hereafter referred to as the Gail model)is a tool for assessing the risk of breast cancer in individuals and its applicability in Asian-American women has not been validated.In this paper,the Gail model was used to predict the risk of breast cancer in patients with BI-RADS 4,and find the risk-distribution threshold of the Gail model of the BI-RADS type 4.The applicability of the Gail model in female population in China was explored.Treatment of molybdenum target BI-RADS 4 patients provides a more reasonable reference.Methods: Through a retrospective survey,we collected taked breast-mammography from our hospital from January 2014 to December 2017 and identified it as BI-RADS 4 and performed breast mass surgery in our hospital(including puncture,Mamotomme and rotary biopsy),surgical biopsy,406 female patients with pathological diagnosis,and 7 assessments of accurate and complete Gail model(including age,age of menarche,primiparous age,history of breast disease,family history,breast biopsy)Patients,ethnicity,collect clinical pathological data of patients,use ROC curve method to determine the risk of breast cancer risk in the risk assessment model of Gail breast cancer in BI-RADS 4 patients,and calculate the breast cancer of BI-RADS 4 patients with different risk levels.The difference in cancer incidence rate,the difference in risk of breast cancer between different risk levels and different BI-RADS4 patients was calculated,P<0.05 was considered statistically significant.Results: 1.In all of the 406 patients in this study,269 were pathologically malignant and 137 were benign.2.The Gail model predicts the risk of personal breast cancer ≥1.67% as high risk.Among the 406 patients,the malignancy rate of the high-risk group is 91.67%,and the malignancy rate of the low-risk group is 65.48%.Statistical significance(P=0.114>0.05).3.The risk value was predicted by all patients’ Gail model,and the ROC curve was drawn.The area under the ROC curve was 0.626,95% confidence interval(0.570,0.681),and0.8% was the new risk threshold,which was divided into high and low risk.There were 155 patients in the high-risk group and 251 in the low-risk group.The difference between the two groups was P=0.000<0.05,and the difference was statistically significant.4.After decomposing the BI-RADS 4 patients into4 a,4b,and 4c groups with a threshold of 0.8%,the sensitivity of the Gail model applied to the risk assessment of the 4a patients was 50.65%,and the specificity was 80.56.%,(P=0.000<0.05,statistically significant),the area under the ROC curve was 0.707,95% confidence interval(0.627,0.778);the sensitivity of the Gail model for risk assessment in patients with type 4b was 50.50%,specificity At 74.77%,(P=0.007<0.05,statistically significant),the area under the ROC curve was 0.632,95% confidence interval(0.549,0.710);the sensitivity of the Gail model for risk assessment in 4c patients was 34.07%.The specificity was83.33%,(P=0.239>0.05,no statistical significance),the area under the ROC curve was 0.588,95% confidence interval(0.490,0.681).Conclusion: At a threshold of 1.67%,the Gail model has a lower overall accuracy rate for breast cancer risk prediction in women with breast mammography target BI-RADS 4;Gail model for mammography target BI-at0.8% risk threshold The overall accuracy of risk prediction for breast cancer in women with RADS 4 is high,especially for the sensitivity and specificity of risk assessment in patients with type 4a and 4b,but not for the sensitivity and specificity of risk assessment for patients with type 4c.High,therefore,the Gail model is of greater value in the risk assessment of patients with mammography target BI-RADS 4 a and 4b,and can effectively predict the risk of breast cancer in such women. |
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