| Objective This study designs to investigate the clinicopathological factors of having 1~2sentinel lymph nodes(SLNs)positive with different molecular subtypes of breast cancer and avoiding axillary lymph node dissection(ALND).The Memorial Sloan-Kettering Cancer Center(MSKCC)model was used to predict the Non-sentinel lymph node(NSLN)metastatic ability of 1~2 SLN positive breast cancer patients with different molecular typing.To compare the accuracy of 8th edition prognostic staging and 7th edition anatomical staging in evaluating the prognosis of 1~2 SLN positive breast cancer with different molecular subtypes and provide the basis for accurate clinical diagnosis and treatment.Methods A retrospective analysis conducts on 917 cases of breast cancer patients confirmed by pathology admitted to the Affiliated Hospital of Inner Mongolia Medical University and the Affiliated People’s Hospital of Inner Mongolia Medical University from June 2009 to June 2018,Loss of follow-up of 16 cases,a total of 901 patients were finally included in the grouping.According to the positive number of SLN pathological results,627 cases were SLN negative,274 cases were 1~2 SLN positive.According to the biological indicators,breast cancer divides into five subtypes.It is Luminal A,Luminal B(HER-2 negative),HER-2 positive(HR-positive),HER-2 positive(HR negative),and triple-negative breast cancer(TNBC).The contents of this study included: 1.The difference of non-sentinel lymph node(NSLN)metastasis and clinicopathological features between 1~2 SLNs positive breast cancer patients with different molecular types;2.The Memorial Sloan-Kettering Cancer Center(MSKCC)was used to assess the risk of NSLN metastasis in 1~2 SLNs positive breast cancer patients;3.The 8th edition prognostic staging and the 7th edition anatomical staging usees to evaluate the prognosis accuracy of 1~2 SLNs positive breast cancer patients with different molecular types.Results 1.Among the 901 breast cancer patients,the negative rate of SLN was 69.59%(627/901),and the positive rate of 1~2 SLNs was 30.41%(274/901).Among 274 cases of 1~2SLNs positive patients,NSLN metastasis rate was 36.9%(101/274).The metastasis rate of one SLN positive NSLN was 27.1%(51/188);the metastasis rate of two SLNs positive NSLN was 58.1%(50/86).The NSLN metastasis rate of patients with Luminal B(HER-2 negative)breast cancer was significantly higher than that of patients with Luminal A(P=0.010)and TNBC(P=0.011).The NSLN metastasis rate of patients with HER-2 positive(HR-positive)breast cancer was significantly higher than that of Luminal A(P=0.002)and TNBC patients(P=0.003).Univariate analysis showed that histological grade(P<0.001),number of SLN positive(P < 0.001),SLN detection method(P=0.002),and molecular types(P=0.003)associates with NSLN metastasis of 1~2 SLNs positive breast cancer.Logistic multivariate analysis showed that: number of SLN positive(OR: 4.022,95%CI: 2.348~6.889,P<0.001),SLN detection method(OR: 3.846,95%CI: 1.541~9.600,P=0.004),histological grade(P=0.001)and molecular type(P=0.004)were independent influencing factors of NSLN metastasis in 1~2 SLNs positive breast cancers.2.The MSKCC model predicts that the area under the curve(AUC)of NSLN metastasis in 1~2 SLNs positive breast cancer patients is0.7148 and 95% confidence interval(CI)is 0.6495 to 0.7802.3.There were significant differences in the 8th edition prognostic staging and the 7th edition anatomical staging of 1~2SLNs positive breast cancer patients with different molecular types(P < 0.001).Conclusions1.The positive rate of NSLN was higher in patients with Luminal B(HER-2 negative)and HER-2 positive(HR-positive).The number of SLN metastases,SLN detection method,histological grade,and molecular typing were independent influencing factors of NSLN metastases.2.The MSKCC model has a preferable ability to predict the NSLN metastasis in1~2 SLNs positive breast cancers with different molecular types.3.In assessing the prognosis of breast cancer,the 8th edition prognostic staging system is more accurate than the 7th edition anatomical staging system. |