Oestrogen receptor status, treatment and breast cancer prognosis in Icelandic BRCA2 mutation carriers
Bibliographic record
Abstract
BACKGROUND: The impact of an inherited BRCA2 mutation on the prognosis of women with breast cancer has not been well documented. We studied the effects of oestrogen receptor (ER) status, other prognostic factors and treatments on survival in a large cohort of BRCA2 mutation carriers. METHODS: We identified 285 breast cancer patients with a 999del5 BRCA2 mutation and matched them with 570 non-carrier patients. Clinical information was abstracted from patient charts and pathology records and supplemented by evaluation of tumour grade and ER status using archived tissue specimens. Univariate and multivariate hazard ratios (HR) were estimated for breast cancer-specific survival using Cox regression. The effects of various therapies were studied in patients treated from 1980 to 2012. RESULTS: Among mutation carriers, positive ER status was associated with higher risk of death than negative ER status (HR=1.94; 95% CI=1.22-3.07, P=0.005). The reverse association was seen for non-carriers (HR=0.71; 95% CI: 0.51-0.97; P=0.03). CONCLUSIONS: Among BRCA2 carriers, ER-positive status is an adverse prognostic factor. BRCA2 carrier status should be known at the time when treatment decisions are made.
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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 | 0.000 | 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".