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

医学 乳腺癌 哨兵节点 腋窝淋巴结 前哨淋巴结 腋窝 逻辑回归 回顾性队列研究 单变量分析 活检 放射科 淋巴结 阶段(地层学) 外科 多元分析 内科学 癌症 古生物学 生物
作者
Victoria Ngai,Justina Cheh Juan Tai,Saima Taj,Heba Khanfar,Elefterios Sfakianakis,Athanasios Bakalis,Rose Baker,Muneer Ahmed
出处
期刊:Breast Cancer Research and Treatment [Springer Science+Business Media]
卷期号:195 (2): 161-169 被引量:3
标识
DOI:10.1007/s10549-022-06672-7
摘要

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.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.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).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.

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