Meta-analysis of sentinel lymph node biopsy in breast cancer

J Surg Res. 1999 Jun 15;84(2):138-42. doi: 10.1006/jsre.1999.5629.


Background: Sentinel lymph node biopsy (SLNB) is a minimally invasive way to diagnose axillary lymph node (ALN) metastases in breast cancer. The most important features are ability to identify the SLN (I.D. rate), how often the SLN and ALN pathology match (concordance), and how often the SLN is negative for cancer when the ALNs are positive (false negative). Technique and patient criteria for SLNB vary among studies. This study performed meta-analysis of published studies to determine the I.D., concordance, and false negative rate (1) overall and for (2) both blue dye and radiocolloid, (3) the injection method, (3) palpable and nonpalpable ALNs, and (4) invasive and in situ disease.

Methods: Inclusion criteria were patients with breast cancer who had SLNB followed by ALN dissection with H&E staining. Meta-analysis was performed using analysis of variance with each observation weighted inversely to its variance. P < 0.05 was considered significant.

Results: Eleven studies (n = 912) met the inclusion criteria. Overall, 762 (84%) SLNs were identified, concordance was 747/762 (98%), and 15/296 (5%) were falsely negative. Highest I.D. rates (P < 0.05) were reported with albumin radiocolloid or dye + radiocolloid (97 and 94%, respectively), with injection around an intact tumor (96%), with invasive cancer (95%), and in the clinically negative axilla (96%). Concordance and false negative rates did not vary.

Conclusions: The SLN can be identified in over 97% of patients if certain techniques and inclusion criteria are used. SLNB reflects the status of the axilla in 97% of cases and has a 5% false negative rate.

Publication types

  • Meta-Analysis

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Axilla
  • Biopsy / adverse effects
  • Breast Neoplasms / pathology*
  • False Negative Reactions
  • Female
  • Humans
  • Lymph Node Excision
  • Lymph Nodes / pathology*
  • Middle Aged