Bilateral mastectomy and breast cancer mortality for invasive lobular carcinoma: A SEER-based study.
Bibliographic record
Abstract
585 Background: Many women with unilateral breast cancer opt for bilateral mastectomy. While removing the unaffected contralateral breast lowers the risk of second primary cancers, there is no benefit on breast cancer mortality. Studies have not investigated whether this holds true for invasive lobular carcinoma (ILC). To estimate the 20-year risk of breast cancer mortality in women with stage I-III unilateral ILC and compare survival outcomes between unilateral lumpectomy, unilateral mastectomy and bilateral mastectomy. Methods: This retrospective cohort study used the Surveillance, Epidemiology, and End Results (SEER) database to identify women diagnosed with unilateral invasive lobular carcinoma (ILC) between 2000 and 2020. The cohort was followed for up to 20 years to assess contralateral breast cancer and breast cancer-specific survival. We estimated crude mortality rates, 20-year cumulative breast cancer mortality, and hazard ratios by surgical treatment group. Kaplan-Meier was used for cumulative risk, and Cox proportional hazards models for unadjusted and adjusted hazard ratios with 95% confidence intervals. P-values < 0.05 were considered significant. Results: We identified 58,861 women with unilateral ILC. Of which, 34,561 (59%) had lumpectomy, 18,894 (32%) had unilateral mastectomy, and 5406 (9.1%) had bilateral mastectomy. The mean age (in years) was 64 ±11 for unilateral lumpectomy, 62 ±13 for unilateral mastectomy, and 57±11 for bilateral mastectomy (p < 0.0001). The mean tumour size was smallest in the lumpectomy group (1.9±1.5 cm) compared with 3.6± 3 cm in both unilateral and bilateral mastectomy groups (p < 0.0001). The 20-year cumulative invasive contralateral breast cancer risk was 7.3% for lumpectomy, 7.5% for unilateral mastectomy, and 0.3% for bilateral mastectomy. The 20-year cumulative breast cancer mortality was 13.4% in the lumpectomy group, 30.2% in unilateral mastectomy group and 24.3% in bilateral mastectomy group. However, after adjusting for demographic, clinical, and treatment variables, we observed no difference in breast cancer mortality rates among unilateral mastectomy patients versus lumpectomy patients (adjusted hazard ratio [aHR], 1.01; 95% CI, 0.94–1.08), and a statistically significant reduction in breast cancer mortality rates among bilateral mastectomy patients compared to lumpectomy patients (aHR, 0.90; 95% CI, 0.82–1.00; p value 0.04). Conclusions: In this cohort of invasive lobular breast cancer, bilateral mastectomy patients had a significantly lower risk of contralateral breast cancer and, after adjusting for differences in the surgical treatment groups, had a 10% lower rate of breast cancer mortality as compared to lumpectomy patients.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".