A prospective evaluation of the sentinel node mapping algorithm in endometrial cancer and correlation of its performance against endometrial cancer risk subtypes

Abstract

ObjectiveSentinel node mapping is emerging as the alternative to lymphadenectomy in endometrial cancer. The objective of our study is to validate of the sentinel node mapping surgical algorithm and also to compare the performance of the algorithm against endometrial cancer risk subtypes DesignThis is a prospective interventional study carried out at a Single University teaching hospital. All patients with apparent early stage endometrial cancer who underwent robotic assisted surgical staging were included. Intracervical injection of Indocyanine Green dye and sentinel node identification and biopsy was done for all study patients. The node positive rate when using SLN mapping alone versus SLN mapping algorithm were compared. The node positivity was compared against various risk subtypes of endometrial cancer. Results69 patients were included in the study. In 95.7% patients SLN was detected with a bilateral detection rate of 87.9%. 10 patients had nodal positivity, among which 7 were identified by SLN mapping alone. The algorithm captured all 10 patients with positive LNs, yielding a node positivity rate of 14.9%, sensitivity and NPV of 100%. For SLN mapping alone the sensitivity was 77.8%, false negative rate (FNR) 22.2%, and NPV 96.6%. In low- and intermediate-risk subtypes SLN mapping as well as algorithm identified all node positive patients, but in high-risk endometrial cancers the SLN mapping technique alone had a sensitivity of 57.1% and false-negative rate of 42.9% when compared with 100% sensitivity for the SLN mapping algorithm. ConclusionsWhen doing SLN mapping and biopsy during endometrial cancer staging surgery it is essential that the steps mentioned in the SLN mapping algorithm are followed as SLN mapping alone seems to have a limitation in detecting positive nodes especially in high risk subtypes of endometrial cancer. Even with the lack of survival data, based on the performance of SLN mapping surgical algorithm (even if ultrastaging facility is not available), it seems to be a better technique in detecting metastatic nodes, giving prognostic information, and enabling accurate adjuvant treatment.