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Axillary Recurrence After a Negative Sentinel Node Biopsy for Breast Cancer: Incidence and Clinical Significance

Department of Surgical Oncology, C22, Canisius Wilhelmina Hospital, PO Box 9015, 6500 GS Nijmegen, The Netherlands

Correspondence: Address correspondence and reprint requests to: Marjolein L. Smidt, MD; E-mail: marjoleinsmidt{at}yahoo.com

Background: Sentinel lymph node biopsy (SLNB) carries the inherent risk of approximately 5% false-negative sampling. Undetected tumor-positive nodes of clinical importance are those that lead to axillary recurrence. This survey aims at clarifying the extent of this problem in current practice and literature.

Methods: In a regional teaching hospital, 696 consecutive breast cancer patients underwent SLNB between January 1998 and July 2003, and data were entered in a prospective database. PubMed and the Cochrane library were searched for a systematic review of the literature. Thirteen studies dealt with the follow-up of a cohort of sentinel lymph node (SLN)-negative patients or presented a case report.

Results: The SLN identification rate was 97.1%. The SLN was tumor free in 439 (65%) of the 676 patients. After a median follow-up of 26 months, axillary recurrence was detected in 2 of 439 patients 4 and 27 months after the SLNB. The incidence of clinically apparent false-negative SLNB is .46%. The systematic review resulted in 3184 SLNB-negative patients with a median follow-up of 25 months. Axillary recurrence occurred in eight patients after a median of 21 months. The axillary recurrence rate in the literature is .25%. One third of these patients present with synchronous systemic metastases.

Conclusions: Axillary recurrences after a negative SLNB occur, but at a much lower rate than would be expected on the basis of historical figures and the false-negative SLN findings. The natural history of axillary relapse after negative SLNB resembles the locoregional recurrence of breast cancer.

Key Words: Breast neoplasms • Sentinel lymph node biopsy • Neoplasm recurrence • False negative sampling

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