Non-invasive predictors of axillary lymph node burden in breast cancer: a single-institution retrospective analysis

Victoria Ngai; Justina Cheh Juan Tai; Saima Taj; Heba Khanfar; Elefterios Sfakianakis; Athanasios Bakalis; Rose Baker; Muneer Ahmed

doi:10.1007/s10549-022-06672-7

Non-invasive predictors of axillary lymph node burden in breast cancer: a single-institution retrospective analysis

Breast Cancer Res Treat. 2022 Sep;195(2):161-169. doi: 10.1007/s10549-022-06672-7. Epub 2022 Jul 21.

Authors

Victoria Ngai^#^{1

2}, Justina Cheh Juan Tai^#³, Saima Taj⁴, Heba Khanfar⁴, Elefterios Sfakianakis⁴, Athanasios Bakalis⁴, Rose Baker⁵, Muneer Ahmed^{6

7}

Affiliations

¹ University College London Medical School, London, UK. victoria.ngai.18@ucl.ac.uk.
² Division of Surgery and Interventional Science, University College London, London, UK. victoria.ngai.18@ucl.ac.uk.
³ University College London Medical School, London, UK.
⁴ Department of Breast Surgery, Royal Free London NHS Foundation Trust, London, UK.
⁵ Department of Statistics, School of Business, University of Salford, Salford, UK.
⁶ Division of Surgery and Interventional Science, University College London, London, UK. muneer.ahmed@ucl.ac.uk.
⁷ Department of Breast Surgery, Royal Free London NHS Foundation Trust, London, UK. muneer.ahmed@ucl.ac.uk.

^# Contributed equally.

Abstract

Purpose: Axillary staging is an important prognostic factor in breast cancer. Sentinel lymph node biopsy (SNB) is currently used to stage patients who are clinically and radiologically node-negative. Since the establishment that axillary node clearance (ANC) does not improve overall survival in breast-conserving surgery for patients with low-risk biological cancers, axillary management has become increasingly conservative. This study aims to identify and assess the clinical predictive value of variables that could play a role in the quantification of axillary burden, including the accuracy of quantifying abnormal axillary nodes on ultrasound.

Methods: A retrospective analysis was conducted of hospital data for female breast cancer patients receiving an ANC at our centre between January 2018 and January 2020. The reference standard for axillary burden was surgical histology following SNB and ANC, allowing categorisation of the patients under 'low axillary burden' (2 or fewer pathological macrometastases) or 'high axillary burden' (> 2). After exploratory univariate analysis, multivariate logistic regression was conducted to determine relationships between the outcome category and candidate predictor variables: patient age at diagnosis, tumour focality, tumour size on ultrasound and number of abnormal lymph nodes on axillary ultrasound.

Results: One hundred and thirty-five patients were included in the analysis. Logistic regression showed that the number of abnormal lymph nodes on axillary ultrasound was the strongest predictor of axillary burden and statistically significant (P = 0.044), with a sensitivity of 66.7% and specificity of 86.8% (P = 0.011).

Conclusion: Identifying the number of abnormal lymph nodes on preoperative ultrasound can help to quantify axillary nodal burden and identify patients with high axillary burden, and should be documented as standard in axillary ultrasound reports of patients with breast cancer.

Keywords: Axillary lymph node dissection; Axillary staging; Axillary ultrasound; Breast cancer; Sentinel lymph node biopsy.

MeSH terms

Axilla / pathology
Breast Neoplasms* / diagnostic imaging
Breast Neoplasms* / surgery
Female
Humans
Lymph Node Excision
Lymph Nodes / diagnostic imaging
Lymph Nodes / pathology
Lymph Nodes / surgery
Lymphatic Metastasis / pathology
Retrospective Studies
Sentinel Lymph Node Biopsy