A multicenter study of laparoscopic versus laparotomic surgery in the treatment of stage I adult granulosa cell and Sertoli-Leydig cell tumors: (LARGES): Gynecologic Oncology Research Investigators coLLaborAtion study (GORILLA-3005)

Abstract

Objective. This study aimed to compare the oncologic outcomes between minimally invasive surgery (MIS) and laparotomic surgery in stage I adult granulosa cell tumors (aGCTs) and Sertoli-Leydig cell tumors (SLCTs). Methods. A total of 337 patients with aGCTs (n = 288) and SLCTs (n = 49) between February 2001 and April 2022 were included. Clinicopathological features were evaluated to determine their association with recurrence. Disease-free survival (DFS) was estimated using the Kaplan-Meier method. Prognostic factors for DFS were determined using the Cox proportional hazards regression model with backward elimination. Results. The median follow-up time was 53.0 months (range, 6-230 months). Of the 157 patients who underwent laparotomy, 12 (7.6%) experienced disease recurrence (7 peritoneal seedings). Among the 180 patients who underwent laparoscopic surgery, 21 (11.7%) showed disease recurrence (15 peritoneal seedings). The 10-year DFS rates were significantly different between the two groups (74.3% vs. 53.9%, p = 0.040). In multivariate analysis, the risk factors associated with disease recurrence were International Federation of Gynecology and Obstetrics stage IC (odds ratio [OR], 3.058; 95% confidence interval [CI], 1.482-6.312; p = 0.002) and ovarian tumor morcellation (OR, 2.848; 95% CI, 1.432-5.663; p = 0.003). Conclusions. In stage I aGCTs and SLCTs, FIGO stage IC and tumor morcellation were independently associated with worse DFS. Although MIS itself was not independently associated with DFS after adjustment, tumor morcellation occurred more frequently in the MIS group. These findings highlight the importance of careful surgical approach selection and strict adherence to oncologic principles, particularly intact tumor resection and avoidance of tumor morcellation, when considering MIS. (c) 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.