Learning curves for breast cancer sentinel lymph node mapping based on surgical volume analysis

Implementation of new procedures, including lymphatic mapping for breast cancer, must be done and overseen by the medical community in a responsible way to ensure that the procedures are performed correctly. This study addresses the issues of adequacy of training and certification of surgeons performing lymphatic mapping. Ensuring quality in surgical care requires outcomes measures that are described in this study.

Sixteen surgeons performed lymphatic mapping in 2,255 patients with breast cancer using a combination blue dye and Tc99m-labeled sulfur colloid to identify the sentinel lymph nodes (SLNs). All participants were trained in a 2-day CME-accredited course. The Cox learning curve model (total number of mapping failures/total number of mapping cases) for a consecutive series of lymphatic mapping cases is described. The relationship of the Surgical Volume Index, the cases performed in a 30-day period, to the failure rate for each surgeon was modeled as a logistic regression curve (y = e(a+bx)/[1 + e(a+bx)]).

Surgeons performing less than three SLN biopsies per month had an average success rate of 86.23% +/- 8.30%. Surgeons performing three to six SLN biopsies per month had a success rate of 88.73% +/- 6.36%. Surgeons performing more than six SLN biopsies per month had a success rate of 97.81% +/- 0.44%.

This experience defines a learning curve for lymphatic mapping in breast cancer patients. Data suggest that increased volumes lead to decreased failure rates. These data provide surgeons performing SLN biopsy with a new paradigm for assessing their skill and adequacy of training and describes the relationship between volume of cases performed and success rate of SLN detection.