Edward Tanner1, Allison Puechl2, Kimberly Levinson3, Laura J Havrilesky2, Abdulrahman Sinno3, Angeles Alvarez Secord2, Amanda N Fader3, Paula S Lee2. 1. The Kelly Gynecologic Oncology Service, Department of Gynecology and Obstetrics, Johns Hopkins Hospital, Baltimore, MD, United States. Electronic address: etanner4@jhmi.edu. 2. Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Duke University Medical Center, Duke Cancer Institute, Durham, NC, United States. 3. The Kelly Gynecologic Oncology Service, Department of Gynecology and Obstetrics, Johns Hopkins Hospital, Baltimore, MD, United States.
Abstract
OBJECTIVES: To evaluate the capability of a novel sentinel lymph node (SLN) mapping algorithm to reduce the need for pelvic lymphadenectomy (PLND) in patients with low-grade (G1-2) endometrial cancer (LGEC). METHODS: Patients with LGEC underwent evaluation according to a novel lymphatic assessment algorithm during hysterectomy with SLN biopsy at two academic gynecologic oncology programs. Side-specific PLND was only performed if ipsilateral SLN mapping failed and high-risk uterine features were identified on frozen section (FS). Side-specific and PLND rates were compared to theoretical PLND rates based on the NCCN EC SLN mapping algorithm. RESULTS: Since 11/2015, 113 LGEC patients have been managed according to the algorithm. SLN mapping was bilateral (81%), unilateral (12%), or neither (6%). Nine patients (8.0%) had LN metastases identified. Of the 21 patients requiring intraoperative FS due to failed SLN mapping, high-risk uterine features were identified in eight (38%). These patients underwent either bilateral (2) or unilateral (6) PLND. Side-specific and overall PLND rates were 5.3% and 7.1%, respectively. If all patients with failed mapping had undergone PLND according to the NCCN algorithm, side-specific and overall PLND rates would have been higher, 12.4% and 18.6%, respectively (P=0.01). All patients who failed to map and did not undergo side-specific PLND had low-risk uterine features on final pathology. CONCLUSIONS: Lymphatic assessment using SLN mapping followed by selective FS to determine need for PLND is feasible. When compared to the NCCN algorithm, this novel "Reflex Frozen Section" strategy eliminates PLND in patients at lowest risk for metastasis without compromising identification of metastatic nodal disease.
OBJECTIVES: To evaluate the capability of a novel sentinel lymph node (SLN) mapping algorithm to reduce the need for pelvic lymphadenectomy (PLND) in patients with low-grade (G1-2) endometrial cancer (LGEC). METHODS:Patients with LGEC underwent evaluation according to a novel lymphatic assessment algorithm during hysterectomy with SLN biopsy at two academic gynecologic oncology programs. Side-specific PLND was only performed if ipsilateral SLN mapping failed and high-risk uterine features were identified on frozen section (FS). Side-specific and PLND rates were compared to theoretical PLND rates based on the NCCN EC SLN mapping algorithm. RESULTS: Since 11/2015, 113 LGEC patients have been managed according to the algorithm. SLN mapping was bilateral (81%), unilateral (12%), or neither (6%). Nine patients (8.0%) had LN metastases identified. Of the 21 patients requiring intraoperative FS due to failed SLN mapping, high-risk uterine features were identified in eight (38%). These patients underwent either bilateral (2) or unilateral (6) PLND. Side-specific and overall PLND rates were 5.3% and 7.1%, respectively. If all patients with failed mapping had undergone PLND according to the NCCN algorithm, side-specific and overall PLND rates would have been higher, 12.4% and 18.6%, respectively (P=0.01). All patients who failed to map and did not undergo side-specific PLND had low-risk uterine features on final pathology. CONCLUSIONS: Lymphatic assessment using SLN mapping followed by selective FS to determine need for PLND is feasible. When compared to the NCCN algorithm, this novel "Reflex Frozen Section" strategy eliminates PLND in patients at lowest risk for metastasis without compromising identification of metastatic nodal disease.
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