A prospective algorithm for pre-operative risk stratification and individualized lymph node assessment in patients with endometrial intraepithelial neoplasia (EIN).

OBJECTIVES: The standard of care surgical management of endometrial intraepithelial neoplasia (EIN) is debated. Because EIN carries a 35-40% risk of underlying carcinoma, omission of lymph node sampling can result in incomplete staging. However, lymph node assessment for all patients results in overtreatment for those without cancer. We developed a preoperative risk-based algorithm to direct sentinel lymph node biopsy (SLNB) in EIN. METHODS: Patients with EIN planning hysterectomy were treated prospectively according to our algorithm. Patients with an endometrial stripe (EMS) ≥ 15 mm by pre-operative ultrasound or "EIN-cannot rule out carcinoma" on pathology underwent indocyanine green (ICG) injection and SLNB. Patients with EMS < 15 mm underwent hysterectomy without SLNB. RESULTS: From August 2022-November 2023, 50 patients with EIN underwent hysterectomy. 48% (24/50) had cancer on final pathology, and 16% (8/50) had high-risk cancers (defined as meeting high-intermediate risk criteria for adjuvant radiation, high grade histology, or stage II or higher). SLNB was performed in 92% (22/24) of patients with cancer, including 100% (8/8) with high-risk cancers. Surgical decision making based on the algorithm had 92% sensitivity for achieving surgical staging of cancer and 100% sensitivity for staging high-risk cancers. The negative predictive value of the algorithm (NPV) to correctly identify patients without cancer was 89%. CONCLUSIONS: A preoperative risk-based algorithm using EMS and pathology results has high sensitivity to identify and direct nodal assessment for patients with EIN at higher risk for endometrial cancer. The algorithm may allow for de-escalation and individualization of surgical treatment for EIN.