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Noninvasive Monitoring of Lesion Size in a Heterologous Mouse Model of Endometriosis
Published on: February 26, 2019
Improved prognostic stratification with the FIGO 2023 endometrial cancer staging system. A multicenter Spanish cohort
Nadia Veiga1, Pablo Padilla-Iserte2, Reyes Oliver3
1Department of Gynecology and Obstetrics, Hospital Universitario de Navarra, Pamplona, Spain.
Objective:
To evaluate the impact of applying the FIGO 2023 staging system compared with FIGO 2009 in a real-world cohort of patients with early-stage endometrial cancer who underwent surgery.
Study Design/Methods:
This multicenter retrospective cohort study included patients with apparent early-stage endometrial cancer diagnosed between 2000 and 2020 across 18 Spanish centers. All patients underwent primary surgery and were classified according to both FIGO 2009 and FIGO 2023 criteria. Stage migration was assessed, and the characteristics of newly defined subgroups were described. Survival outcomes, including overall survival (OS) and progression-free survival (PFS), were compared between classifications.
Results:
A total of 4566 patients were included. Application of the FIGO 2023 system resulted in stage migration in 909 patients (19.9%) compared with FIGO 2009. The FIGO 2023 system showed a higher 5-year OS for Stage I patients than the 2009 classification (91.3% vs. 88.2%). Within the new substages, 5-year OS was 93.9% in Stage IA1 and 91.9% in Stage IA2, and Stage IA3 demonstrated distinct survival outcomes. Overall survival for Stage III remained comparable between classifications, although outcomes varied across subcategories. In a simplified classification (Stages I-III), the FIGO 2023 system showed improved prognostic discrimination for both PFS and OS according to Harrell's C-index.
Conclusions:
The FIGO 2023 staging system leads to substantial reclassification of early-stage endometrial cancer patients and introduces new prognostic subgroups. This increased granularity improves prognostic stratification and may support individualized treatment decisions, even when molecular testing is limited.
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