Impact of Oophorectomy on Cancer Incidence and Mortality in Women With a <i>BRCA1</i> or <i>BRCA2</i> Mutation
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The purposes of this study were to estimate the reduction in risk of ovarian, fallopian tube, or peritoneal cancer in women with a BRCA1 or BRCA2 mutation after oophorectomy, by age of oophorectomy; to estimate the impact of prophylactic oophorectomy on all-cause mortality; and to estimate 5-year survival associated with clinically detected ovarian, occult, and peritoneal cancers diagnosed in the cohort. PATIENTS AND METHODS: Women with a BRCA1 or BRCA2 mutation were identified from an international registry; 5,783 women completed a baseline questionnaire and ≥ one follow-up questionnaires. Women were observed until either diagnosis of ovarian, fallopian tube, or peritoneal cancer, death, or date of most recent follow-up. Hazard ratios (HRs) for cancer incidence and all-cause mortality associated with oophorectomy were evaluated using time-dependent survival analyses. RESULTS: After an average follow-up period of 5.6 years, 186 women developed either ovarian (n = 132), fallopian (n = 22), or peritoneal (n = 32) cancer, of whom 68 have died. HR for ovarian, fallopian, or peritoneal cancer associated with bilateral oophorectomy was 0.20 (95% CI, 0.13 to 0.30; P < .001). Among women who had no history of cancer at baseline, HR for all-cause mortality to age 70 years associated with an oophorectomy was 0.23 (95% CI, 0.13 to 0.39; P < .001). CONCLUSION: Preventive oophorectomy was associated with an 80% reduction in the risk of ovarian, fallopian tube, or peritoneal cancer in BRCA1 or BRCA2 carriers and a 77% reduction in all-cause mortality.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it