Prediction capability of axillary nodal status by five node sampling in early invasive breast cancer

Authors

  • R. S. Gupta Department of Surgery, Gandhi Medical College Bhopal, M.P, India
  • Devendra Chaudhary Department of Surgery, Gandhi Medical College Bhopal, M.P, India
  • Arvind Rai Department of Surgery, Gandhi Medical College Bhopal, M.P, India
  • Arpan Achaudhary Department of Urology, R. G. Kar Medical College and Hospital, Kolkata, India
  • Abhishek Chaube Department of Surgery, Gandhi Medical College Bhopal, M.P, India
  • Rohit Kumar Namdev Department of Surgery, Gandhi Medical College Bhopal, M.P, India

DOI:

https://doi.org/10.18203/2349-2902.isj20160212

Keywords:

Breast cancer, Five node sampling, Sentinel node biopsy, Axillary sampling

Abstract

Background: Management of axilla in early breast cancer is controversial with options being sentinel lymph node biopsy (SLNB), axillary sampling and axillary dissection. In our study we explored the possibilities of 5-node sampling as an alternative or adjunct to SLNB in early invasive breast cancer.

Methods: We did an observational study of the 45 patients, who underwent modified radical mastectomy and compared the initial 5-nodes pathology with standard axillary dissection in the excised breast tissue specimen.

Results: Out of 45 patients, first 5-nodes were found positive in 25 cases. In 8 cases only initial 5-nodes were involved. Sensitivity improved with increasing number of nodes examined in 5-node biopsy, approaching 100% with 5 nodes examined. In all pathological negative axilla, 5-node pathology was also negative.

Conclusions: Five node sampling of axilla has a comparable sensitivity and false negative rate as SLNB. It fairly represents axillary nodal status and could be a good adjunct to SLNB for further increasing accuracy of later. It can also be an alternative to SLNB in situation where lack of feasibility to perform it as in many developing countries. We also recommend further study directly comparing five-node sampling and SLNB in future.

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Published

2016-12-13

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Original Research Articles