88P Bilateral mastectomy and breast cancer mortality
Bibliographic record
Abstract
The impact of bilateral mastectomy in women diagnosed with unilateral breast cancer on reduced deaths from breast cancer is a subject of considerable interest. We sought to estimate the 20-year risk of breast cancer mortality among women with Stage 0 to Stage III unilateral breast cancer according to the type of surgery performed (lumpectomy, unilateral mastectomy, bilateral mastectomy). We identified 661,270 women with unilateral breast cancer in the Surveillance, Epidemiology, and End Results (SEER) 17 database diagnosed from 2000 to 2019. From these, we generated three closely matched cohorts of equal size using 1:1:1 generalized propensity score matching by surgery performed. Matched subjects were followed for 20 years for contralateral breast cancer and for breast cancer mortality. There were 661,270 eligible cases of unilateral breast cancer in our cohort, of which 39,736 (6.0%) underwent a bilateral mastectomy. After matching, we retained three similar cohorts of equal size (n = 36,028). The 20-year cumulative risk of contralateral breast cancer was 7.8% in the lumpectomy group, 6.1% in the unilateral mastectomy group, and 0.7% in the bilateral mastectomy group. In a combined lumpectomy/unilateral mastectomy group, the breast cancer mortality rate was higher after developing a contralateral cancer (HR, 4.00; 95% CI, 3.52-4.54). The 20-year breast cancer mortality was 16.3% in the lumpectomy group, 16.7% in the unilateral mastectomy group, and 16.7% in the bilateral mastectomy group. The risk of dying of breast cancer increases significantly after experiencing a contralateral breast cancer. Women with breast cancer treated with bilateral mastectomy had a greatly diminished risk of contralateral breast cancer, but experienced similar mortality rates as those patients treated with lumpectomy or unilateral mastectomy.
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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 | 0.000 |
| 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".