Evidence map›Paper›PMID 36172144›Full record

ArticleFrontiers in oncology2022

A novel nomogram for decision-making assistance on exemption of axillary lymph node dissection in T1-2 breast cancer with only one sentinel lymph node metastasis.

Lei Liu, Yaoxin Lin, Guozheng Li, Lei Zhang, Xin Zhang, Jiale Wu, Xinheng Wang, Yumei Yang, Shouping Xu

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Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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4 citing papers in PubMed.

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5 · Who and what money

Authors and funding

9 authors.

Lei LiuDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Yaoxin LinChinese Academy of Sciences (CAS) Center for Excellence in Nanoscience, Chinese Academy of Sciences (CAS) Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, National Center for Nanoscience and Technology, Beijing, China.
Guozheng LiDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Lei ZhangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Xin ZhangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Jiale WuDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Xinheng WangDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.
Yumei YangDepartment of The First Operating Room, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Shouping XuDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: T1-2 breast cancer patients with only one sentinel lymph node (SLN) metastasis have an extremely low non-SLN (NSLN) metastatic rate and are favorable for axillary lymph node dissection (ALND) exemption. This study aimed to construct a nomogram-based preoperative prediction model of NSLN metastasis for such patients, thereby assisting in preoperatively selecting proper surgical procedures. Methods: A total of 729 T1-2 breast cancer patients with only one SLN metastasis undergoing sentinel lymph node biopsy and ALND were retrospectively selected from Harbin Medical University Cancer Hospital between January 2013 and December 2020, followed by random assignment into training (n=467) and validation cohorts (n=262). A nomogram-based prediction model for NSLN metastasis risk was constructed by incorporating the independent predictors of NSLN metastasis identified from multivariate logistic regression analysis in the training cohort. The performance of the nomogram was evaluated by the calibration curve and the receiver operating characteristic (ROC) curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram. Results: Overall, 160 (21.9%) patients had NSLN metastases. Multivariate analysis in the training cohort revealed that the number of negative SLNs (OR: 0.98), location of primary tumor (OR: 2.34), tumor size (OR: 3.15), and lymph-vascular invasion (OR: 1.61) were independent predictors of NSLN metastasis. The incorporation of four independent predictors into a nomogram-based preoperative estimation of NSLN metastasis demonstrated a satisfactory discriminative capacity, with a C-index and area under the ROC curve of 0.740 and 0.689 in the training and validation cohorts, respectively. The calibration curve showed good agreement between actual and predicted NSLN metastasis risks. Finally, DCA revealed the clinical utility of the nomogram. Conclusion: The nomogram showed a satisfactory discriminative capacity of NSLN metastasis risk in T1-2 breast cancer patients with only one SLN metastasis, and it could be used to preoperatively estimate NSLN metastasis risk, thereby facilitating in precise clinical decision-making on the selective exemption of ALND in such patients.

Indexed as

axillary lymph node dissectionbreast cancerexemptionnomogramnon-sentinel lymph node

Identifiers

PMID36172144
PMCPMC9511144

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