Ten-Year Real-World Outcomes and Clinicopathologic Predictors of Recurrence in Adult Granulosa Cell Tumors: A Turkish Single-Center Experience
Bibliographic record
Abstract
Adult granulosa cell tumors (AGCT) are rare ovarian neoplasms with typically indolent behavior but potential for late recurrence. This study aimed to evaluate long-term outcomes and identify clinicopathological predictors of disease-free survival (DFS) in patients with AGCTs. This retrospective cohort study included patients with histologically confirmed AGCTs who were treated or followed at Ege University Faculty of Medicine between January 2012 and 2023. Survival outcomes were analyzed using Kaplan–Meier and Cox regression methods. Among 55 patients with a median follow-up of 113.7 months, the median DFS was 92.3 months, and the median overall survival (OS) was 113.7 months. The 5-year DFS and OS rates were 84.5% and 93.9%, respectively. Recurrence occurred in 23.6% of patients and was significantly linked to advanced FIGO stage, atypical endometrial pathology, and bleomycin–etoposide–cisplatin (BEP)/etoposide–cisplatin (EP)-based adjuvant chemotherapy. Larger tumor size (>10 cm) and stage III disease were also associated with shorter DFS. Univariate analysis showed that stage III disease (HR 7.14, p = 0.006) and tumor size >10 cm (HR 3.59, p = 0.025) were associated with significantly shorter DFS, while absence of endometrial pathology was protective (HR 0.34, p = 0.022). In multivariate analysis, stage III disease remained the only independent predictor of recurrence (HR 4.45, p = 0.046). Advanced-stage disease is an independent predictor of recurrence and should be considered a high-risk feature requiring prolonged follow-up.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".