Characteristics and outcome of BRCA mutated epithelial ovarian cancer patients in Italy: A retrospective multicenter study (MITO 21)
Bibliographic record
Abstract
OBJECTIVE: Around 15% of epithelial ovarian cancer (EOC) patients (pts) harbor a germline BRCA1 or 2 mutation, showing different features than BRCA wild-type pts. The clinical and pathological features of an Italian BRCA mutated EOC cohort were described. METHODS: We retrospectively analyzed clinical, pathological and mutational data from a cohort of Italian BRCA mutated EOC pts. treated in 15 MITO centers between 1995 and 2017. RESULTS: Three-hundred thirty-one pts. were recorded. Two-hundred forty (72%) and 91 (27.5%) pts. harbored a BRCA1 and BRCA2 mutation, respectively. Median age at diagnosis was 52 years. The most frequent diagnosis was a high grade serous FIGO III or IV EOC and platinum doublet in first-line was administered to almost all pts. Fifty-three % of them had no residual disease (R = 0) at surgery. Median progression-free-survival (mPFS) after first-line chemotherapy was 29 months. Expected percentage of pts. alive at 5 years was 72.5% (CI 60.2-80.8%) and R = 0 predicted a significantly longer overall survival (OS). Sixty-six pts. (19,9%) had both an EOC and a breast cancer (BC) diagnosis. The first diagnosis was BC in 81,8% of cases with a mean interval between the two diagnoses (IBTDs) of 132.4 months. Mutational data show that the founder mutation c.5266dupC in BRCA1 was the most frequently recorded. CONCLUSIONS: This is the largest Italian BRCA mutEOC cohort. The only predictor of longer OS was R = 0. EOC pts. that developed subsequently a BC are long-term survivors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".