Analysis Of The Factors Associated With Axillary Lymph Node Metastasis In Breast Cancer And Establishment Of An Evaluation Model

Purpose:Relevant indicators were selected from the clinical,imaging,pathology and other commonly used clinical indicators of patients undergoing modified radical mastectomy for breast cancer,and the evaluation score model before axillary lymph node dissection is constructed for breast cancer patients,so as to avoid sentinel lymph node biopsy or axillary lymph node dissection for breast cancer patients with negative axillary lymph nodes to a certain extent.Method:Collect the age,imaging data(lymph node status,tumor location)and pathological data(pathological type,nuclear grade,tumor size,and age)of patients undergoing modified radical mastectomy for breast cancer from January 2015 to December 2019 With or without vascular infiltration,estrogen receptor(ER),progesterone receptor(PR),Her-2,Ki67 status,lymph node status,etc.The clinical and pathological data of breast cancer patients were analyzed retrospectively,and the clinical and pathological indicators related to axillary lymph node metastasis were screened by single factor analysis.The prediction model of axillary lymph node metastasis was established based on the results of multi-factor analysis.The area under the curve and ROC curve obtained by internal verification were used to evaluate the effectiveness of the SSPH model.Results:There were 488 breast cancer patients who met the inclusion criteria.Based on clinical relevant experience and reference to relevant literature,13 clinical indicators were screened.The chi-square test was used to analyze the correlation between each relevant index and lymph node metastasis.Including: tumor size,preoperative lymph node status,tumor location,age,histological nuclear grade,pathological type,vascular infiltration,molecular biotyping,Her-2.The results of multivariate analysis suggested that age,tumor size,vascular infiltration,preoperative lymph node status and mass location were independent predictors of axillary lymph node metastasis in breast cancer.Therefore,this study model included 5 variables,including age,pathological mass size,vascular infiltration,preoperative lymph node status,and mass location.The calculation formula was: logit P=-1.409-0.702A1-0.815A2+0.955B+0.049C1-0.603C2-0.947C3-0.416C4+1.337D1+1.694D2+1.995D3+1.506E(A1 was the middle-aged group,A2 was the elderly group,B was the positive preoperative lymph node status,C1 tumor location was on the outside,C2 was on the outside,C3 was on the inside,lower on the inside of C4,D1 tumor size group T1,D2 was on the inside of T2,D3 was on the 3,and E was vascular infiltration).The working characteristic curve(ROC curve)of the model was drawn.Its AUC was 0.746,and the best predictive value was 0.564.That is,if the probability was greater than the critical value,we judged the patients with axillary lymph node metastasis,with a sensitivity of 0.663 and a specificity of 0.707.After internal Bootstrap verification of the model,the AUC was 0.755 indicating that the results were very stable.Conclusion:The model is effective in predicting axillary lymph node metastasis in breast cancer and has high clinical value.By using this model to predict patients with low rates of axillary lymph node metastasis,sentinel lymph node biopsy or axillary dissection can be avoided to reduce the incidence of postoperative complications of breast cancer.In view of the limitations of this model,SSPH model cannot replace sentinel lymph node biopsy,which is still the most important method to evaluate the status of axillary lymph nodes.