BRCA1/2 Mutation Types Do Not Affect Prognosis in Ovarian Cancer Patients
Bibliographic record
Abstract
Background: High grade serous ovarian carcinoma (HGSOC) is the most lethal type of epithelial ovarian cancer, with a prevalence of germline BRCA1/2 mutations as high as 20%. Our objective is to determine whether the location of mutations in the different domains of the BRCA1/2 genes affects the clinical outcome of HGSOC patients. Methods: A total of 51 women with BRCA1 or BRCA2 mutated ovarian cancer were identified. Progression-free survival (PFS) and overall survival (OS) were analyzed. Results: In our study cohort, 35 patients were carriers of germline mutations in BRCA1 and 16 in BRCA2. The median PFS time following completion of the primary therapy was 23.8 months (95% CI 20.1–27.5) and the median OS was 92.9 months (95% CI 69.8–116.1) in all BRCA carriers. After multivariate analysis, no significant association among the location or type of BRCA1/2 mutation with PFS or OS was identified. Notably, significant differences in PFS between carriers of identical mutations in the same BRCA gene were detected. Conclusions: Among HGSOC patients, BRCA1/2 carriers with mutations in different locations of the genes show no significant difference in survival outcomes, in terms of PFS and OS, suggesting the potential effect of other genetic abnormalities and co-contributing risk factors.
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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 | 0.002 |
| 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) | 0.002 | 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".