Impact of <i><scp>BRCA</scp></i> mutations on outcomes among patients with serous endometrial cancer
Bibliographic record
Abstract
OBJECTIVE: To compare the outcome of patients with uterine papillary serous cancer (UPSC) carrying a BRCA mutation with that of patients with UPSC who are BRCA wild-type. METHODS: The present retrospective, multicenter cohort study included women with UPSC who were diagnosed between January 1, 1993, and December 31, 2014, and were tested for the BRCA mutation at three Israeli medical centers. Data were collected from the medical records, and patient and tumor characteristics and disease outcomes were compared between BRCA mutation carriers and noncarriers. The primary outcome was overall survival. RESULTS: In total, 14 BRCA mutation carriers and 50 noncarriers were included. Both groups had similar treatment modalities (P=0.530). A non-significant trend toward BRCA mutation carriers being diagnosed more frequently at an advanced stage compared with noncarriers was observed (P=0.090). Median overall survival (25 vs 37 months; P=0.442), progression-free survival (37 vs 29 months; P=0.536), and disease-specific survival (60 vs 39 months; P=0.316) were similar between the carrier and noncarrier groups. CONCLUSIONS: Although not significant, BRCA mutation carriers tended to have more advanced disease at diagnosis. However, the survival was similar irrespective of the BRCA status in this small group. Further research is needed to confirm these findings in a larger cohort.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".