Risk Factors And Prediction Of Axillary Lymph Nodal Metastases In Triple-Negative Breast Cancer Patients

BackgroundBreast cancer is the most common cancer among females in the world.Lymph nodal metastasis is the key metastasis way of breast cancer.Triple-negative breast cancer（TNBC）is a highly malignant,aggressive,and heterogeneity subtype that currently lacks effective treatment.Therefore,the further understanding of its occurrence and development,and early prediction of its progress are urgent clinical needs.Establishing the prediction model of axillary lymph nodal metastasis（ALNM）in TNBC patients can assist in individualized treatment and predicting the prognosis.ObjectiveExploring the risk factors of ALNM in TNBC patients and establishing a prediction model,which can serve as mathematical evidence for clinicians to determine individualized treatment and to predict the prognosis of the TNBC patients.MethodsThis thesis retrospectively analyzes the clinicopathological data of 220 TNBC patients in the Second Hospital of Jilin University from January 1^st,2015 to December 31^st,2020.The included patients are randomly divided into two groups with a ratio of 2:1:the modeling group（147 cases）and the validation group（73 cases）,respectively.The chi-square test,student’s t-test,Fisher exact probability method,and Mann-Whitney U test are applied to both groups for univariate analysis.The selected risk factors are then fitted using the binomial Logistic regression for multivariate analysis,which can select independent risk factors.Based on the above statistic results,a nomogram prediction model is established.Finally,the model is validated and assessed.ResultsAmong the 220 TNBC patients,the onset age is 24-80 years old,with an average age of 51.67.Invasive ductal carcinoma is the most common pathological type.Most patients are of histological grade III.80 cases have axillary lymph nodal metastases,and 140 cases without.The p values of all clinicopathological factors between the modeling group and validation group are greater than 0.05,which indicates that the grouping scheme is statistically feasible.The results of the univariate analysis show that the p-value of Ki67,Her-2,and vascular tumor thrombus in both groups are less than 0.05,which indicates a significant difference in those factors between ALNM and non-ALNM patients.Subsequent multivariate analysis screens that Ki67,Her-2,and vascular tumor thrombus are independent risk factors for predicting ALNM in TNBC patients.It can be drawn from the Logistic regression that:Patients with vascular tumor thrombus have a higher risk of ALNM;The risk becomes higher with the increase of Ki67;Compared to patients with Her-2“-”expression,the risk of those with Her-2“+”is 2.861 times,and the risk of those with Her-2“++”is 4.158 times.Based on the analysis results above,a prediction model is established in this thesis,a nomogram is given,and the model is internally validated.The ROC curve,calibration curve,and decision curve analysis（DCA）are used to validate the model.The areas under the curve（AUC）of the modeling group and validation group are 0.735 and 0.777,respectively.The C-Index is 0.777 with a standard deviation of 0.105.The validation results show that the established model can well predict the risk of ALNM in TNBC patients.The prospects of clinical application of the prediction model are further given:The model is of good specificity and low false negative rates（FNRs）.When the cut-off is at 60%,the FNR is 9.09%;When the cut-off is at 70%,the FNR becomes 4.55%.Conclusion1.Three factors,Ki67,Her-2,and vascular tumor thrombus are,are positively correlated with ALNM in TNBC patients.2.There are no significant correlations between ALNM and age,menstrual status,family history of breast cancer,histological grade,pathological type,body mass index（BMI）,p53,CK5/6,EGFR,or E-cadherin.3.The established model can well predict the risk of ALNM in TNBC patients in both modeling and validation groups.