Results of a national training programme in sentinel lymph node biopsy for breast cancer

Authors


Correspondence to: Professor R. E. Mansel, Department of Surgery, School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, UK (e-mail: manselre@cf.ac.uk)

Abstract

Background

New Start, a structured, validated, multidisciplinary training programme in sentinel lymph node biopsy (SLNB), was established to allow the introduction and rapid transfer of appropriate knowledge and technical skills to ensure safe and competent practice across the UK.

Methods

Multidisciplinary teams attended a theory/skills laboratory course, following which they performed 30 consecutive SLNBs, either concurrently with their standard axillary staging procedure (training model A) or as stand-alone SLNB (training model B). SLNB was performed according to a standard protocol using the combined technique of isotope (99mTc-labelled albumin colloid) and blue dye. An accredited New Start trainer mentored the first five procedures in the participant's hospital, or all 30 if stand-alone. Validation standards for model A and B were a localization rate of at least 90 per cent. In addition, for model A only, in which a minimum of ten patients were required to be node-positive, a false-negative rate (FNR) of 10 per cent or less was required.

Results

From October 2004 to December 2008, 210 SLNB-naive surgeons, in 103 centres, performed 6685 SLNB procedures. The overall sentinel lymph node (SLN) localization rate was 98·9 (95 per cent confidence interval 98·6 to 99·1) per cent (6610 of 6685) and the FNR 9·1 (7·9 to 10·5) per cent (160 of 1757). The FNR was related to nodal yield, ranging from 14·8 per cent for one node and declining to 9·7, 6·6, 4·7 and 4·1 per cent for two, three, four and more than four SLNs respectively. No learning curve was identified for localization or FNR.

Conclusion

The programme successfully trained a wide range of UK breast teams to perform safe SLNB and suggested that a standard injection protocol and structured multidisciplinary training can abolish learning curves.

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