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Chinese Journal of Breast Disease(Electronic Edition) ›› 2022, Vol. 16 ›› Issue (06): 327-335. doi: 10.3877/cma.j.issn.1674-0807.2022.06.001

• Original Article •     Next Articles

Risk assessment model for sentinel lymph node and non-sentinel lymph node metastases in patients with invasive breast cancer

Simin Yuan1, Xueying Wang2, Xiangying Xie3, Deyuan Fu2, Jiaxin Zhang2,()   

  1. 1. Graduate School, Dalian Medical University, Dalian 116000, China; Department of Thyroid and Breast Surgery, North Jiangsu People’s Hospital, Yangzhou 225000, China
    2. Department of Thyroid and Breast Surgery, North Jiangsu People’s Hospital, Yangzhou 225000, China
    3. Department of Nursing, People’s Hospital of Wuhan University, Wuhan 430060, China
  • Received:2022-03-31 Online:2022-12-01 Published:2023-01-31
  • Contact: Jiaxin Zhang

Abstract:

Objective

To investigate the risk factors for sentinel lymph node and non-sentinel lymph node metastasis in patients with invasive breast cancer, establish a visual nomogram model and guide clinical axillary management.

Methods

A retrospective analysis was performed in 497 patients with pathologically confirmed invasive breast cancer in the Department of Thyroid and Breast Surgery, North Jiangsu People’s Hospital from 2017 to 2020. Sentinel lymph node biopsy is performed in all patients. Univariate and multivariate logistic regression analysis was used to screen risk factors for sentinel and non-sentinel lymph node metastasis. The nomogram model and receiver operating characteristic (ROC) curve were drawn by the R 4.1.0 software, and the area under the curve (AUC) was calculated, and the calibration curve was created by the Calibrate function in the rms package to test the predictive effect of the model.

Results

Among 497 patients, 221 (44.5%) had sentinel lymph node metastasis and they all underwent axillary lymph node dissection (ALND). Among them, 141 cases had non-sentinel lymph node metastasis confirmed by routine pathological examination after surgery. Univariate analysis showed that albumin-to-globulin ratio (Z=-2.000, P=0.046), peripheral blood neutrophil-to-lymphocyte ratio (NLR) (Z=-2.137, P=0.033), histological grade (Z=-5.168, P<0.001), intravascular cancer thrombus (χ2=114.010, P<0.001), HER-2 (χ2=3.989, P=0.046), Ki-67 (χ2=6.860, P=0.009), mass location (χ2=72.593, P<0.001) were related to sentinel lymph node metastasis. Multivariate analysis showed that histological grade (grade 3 vs grade 1: OR=3.167, 95%CI: 1.201-8.356, P=0.002), intravasculature cancer thrombus (OR=9.115, 95%CI: 5.487-15.142, P<0.001), and mass location (upper outer quadrant vs upper inner quadrant: OR=0.133, 95%CI: 0.063-0.618, P<0.001) were independent predictors of sentinel lymph node metastasis. The 221 patients receiving ALND were divided into non-sentinel node metastatic group and non-metastatic group. Univariate analysis showed that lump size (χ2=9.406, P=0.002), peripheral blood neutrophil count (Z=-2.248, P=0.025), histological grade (Z=-3.270, P=0.001) and intravascular cancer thrombus (χ2=12.959, P<0.001) were related to non-sentinel lymph node metastasis. Multivariate analysis showed that mass size (OR=2.600, 95%CI: 1.420-4.760, P=0.002), intravascular cancer thrombus (OR=2.968, 95%CI: 1.640-5.369, P<0.001) and peripheral blood neutrophil count (OR=1.336, 95%CI: 1.060-1.684, P=0.014) were independent predictors of non-sentinel lymph node metastasis. The AUC of ROC curve was 0.828 (95%CI: 0.793-0.865) for sentinel lymph node and 0.712 (95%CI: 0.642-0.782) for non-sentinel lymph node metastasis. The C-index of the calibration curve was 0.828 for sentinel lymph node and 0.712 for non-sentinel lymph node metastasis, indicating high consistence with the actual results.

Conclusion

The nomogram model can predict the probability of sentinel and non-sentinel lymph node metastasis, providing guidance for precision axillary treatment in clinic.

Key words: Breast neoplasms, Sentinel lymph nodes, Nomograms

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