Robotic blue-dye sentinel lymph node detection for endometrial cancer - Factors predicting successful mapping

Sentinel lymph node (SLN) mapping has emerged as a viable option for the treatment of patients with endometrial cancer. We report our initial experience with SLN mapping algorithm, and examine the factors predicting successful SLN mapping.

We analyzed all data recorded in our institute on robotic blue-dye SLN detection mapping from the time it was first introduced to our department in January 2012-December 2014. Data included patient demographics, SLN allocation, operating room times, and pathology results.

During the study period, 74 patients had robotic assisted surgery for endometrial cancer with attempted SLN mapping. SLN was found overall in 46 patients (62.1%). At first, SLN was detected in only 50% of cases, but after performing 30 cases, detection rates rose to 84.6% (OR = 3.34, CI 1.28-8.71; p = 0.003). Univariate analysis showed a higher detection rate with methylene blue than patent blue dye, 74.3% vs. 52.3% (OR = 2.744, 95% CI 1.026-7.344; p = 0.042). In multivariate analysis, high body mass index (BMI) was associated with failed mapping (OR = 0.899; 95% CI 0.808-1.00), as was the presence of lymph-vascular space invasion (LVSI) (OR = 0.126; 95% CI 0.24-0.658) and few cases per surgeon (OR = 1.083, 95% CI 1.032-1.118). Factors related to uterine pathology itself, including tumor histology, grade, method of diagnosis, the presence of an endometrial polyp, and lower uterine segment involvement were not found to be associated with successful mapping.

Surgeon experience, BMI and LVSI may affect the success rate of SLN mapping for endometrial cancer. These factors should be investigated further in future studies.