Sep 29

PQA 06 - Genitourinary Cancer, Gynecological Cancer, and Health Care Access and Engagement

3737 - Exploring the Molecular Classification-Based Personalized Treatment Decision-Makings in FIGO Stage I-III Endometrial Carcinoma after Surgery

02:15pm - 03:30pm ET

Poster Hall - Exhibit Hall A

Screen: 29

Presenter(s)

Lingxia Xin, MD - eking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, Beijing,

L. Xin¹, K. Ren¹, Z. Yan¹, Y. Sheng¹, Y. Wang¹, Y. Zhang¹, X. Hou¹, H. Wu², and F. Zhang¹; ¹Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China, ²Department of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

Purpose/Objective(s): Personalized management strategies for endometrial carcinoma (EC) are increasingly recognized and implemented in clinical practice, aiming to mitigate both overtreatment and undertreatment. However, robust real-world evidence supporting this approach remains limited. This study aims to assess whether molecular classification can inform personalized treatment decisions for EC by presenting real-world data on survival outcomes and recurrence patterns.

Materials/Methods: This retrospective cohort study included patients with International Federation of Gynecology and Obstetrics (FIGO) stage I-III EC who underwent primary surgical treatment and had available molecular classification results between December 2017 and April 2025. A cost-effective molecular classification approach was utilized. General adjuvant treatment principles followed the ESGO-ESTRO-ESP 2021 guideline. Personalized adjuvant therapy strategies were determined collaboratively through a multidisciplinary approach involving a senior gynecologist, radiation oncologist, and pathologist, integrating clinical, pathological, and molecular classification data. Survival outcomes were evaluated, dynamic annual hazard rates (AHRs) were visualized, and recurrence patterns were compared across subgroups. Independent prognostic factors were identified using Cox regression analyses.

Results: Among the 267 patients included, the NSMP subtype was most prevalent (46.8%), followed by MMRd (27.7%), POLEmut (13.1%), and p53abn (12.4%). Endometrioid carcinoma G1-2 was the predominant histological type (74.5%). Conversely, within the p53abn subgroup, endometrioid carcinoma G3 was most frequent (42.4%). According to the FIGO 2009 staging system, the distribution was: IA (66.7%), IB (20.6%), II (4.5%), and III (12.2%). Restaging using the FIGO 2023 criteria resulted in upstaging in 20.2% of patients and downstaging in 2.6%. The majority of patients (56.6%) were classified as low-risk per the ESGO-ESTRO-ESP 2025 risk classification system. While observation alone was employed in 45.7% of the overall cohort, intensified treatment was administered to 33.3% of patients in the p53abn subgroup. The 3-year overall survival (OS) and disease-free survival (DFS) for the entire cohort were excellent at 99.2% and 88.4%, respectively. The p53abn group exhibited the highest proportion of recurrence (30.3%), frequently presenting as simultaneous multi-site recurrences. Both the ESGO-ESTRO-ESP 2025 risk classification and the FIGO 2023 staging system were identified as independent prognostic factors for recurrence.

Conclusion: This study provides evidence that personalized treatment decisions guided by molecular classification are feasible and can lead to excellent survival outcomes in patients with stage I-III EC.