Axillary Ultrasound Accurately Excludes Clinically Significant Lymph Node Disease in Patients With Early Stage Breast Cancer
- PMID: 26779976
- PMCID: PMC4947031
- DOI: 10.1097/SLA.0000000000001549
Axillary Ultrasound Accurately Excludes Clinically Significant Lymph Node Disease in Patients With Early Stage Breast Cancer
Abstract
Objective: Assess the performance characteristics of axillary ultrasound (AUS) for accurate exclusion of clinically significant axillary lymph node (ALN) disease.
Background: Sentinel lymph node biopsy (SLNB) is currently the standard of care for staging the axilla in patients with clinical T1-T2, N0 breast cancer. AUS is a noninvasive alternative to SLNB for staging the axilla.
Methods: Patients were identified using a prospectively maintained database. Sensitivity, specificity, and negative predictive value (NPV) were calculated by comparing AUS findings to pathology results. Multivariate analyses were performed to identify patient and/or tumor characteristics associated with false negative (FN) AUS. A blinded review of FN and matched true negative cases was performed by 2 independent medical oncologists to compare treatment recommendations and actual treatment received. Recurrence-free survival was described using Kaplan-Meier product limit methods.
Results: A total of 647 patients with clinical T1-T2, N0 breast cancer underwent AUS between January 2008 and March 2013. AUS had a sensitivity of 70%, NPV of 84%, and PPV of 56% for the detection of ALN disease. For detection of clinically significant disease (>2.0 mm), AUS had a sensitivity of 76% and NPV of 89%. FN AUS did not significantly impact adjuvant medical decision making. Patients with FN AUS had recurrence-free survival equivalent to patients with pathologic N0 disease.
Conclusions: AUS accurately excludes clinically significant ALN disease in patients with clinical T1-T2, N0 breast cancer. AUS may be an alternative to SLNB in these patients, where axillary surgery is no longer considered therapeutic, and predictors of tumor biology are increasingly used to make adjuvant therapy decisions.
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