Survival Differences in Women with and without Autologous Breast Reconstruction after Mastectomy for Breast Cancer
Bibliographic record
Abstract
Background: Breast reconstruction (BR) is an option for women who are treated with mastectomy; however, there has been concern regarding the oncologic safety of BR. In this study, we evaluated recurrences and mortality in women treated with mastectomy and compared outcomes in those treated with mastectomy alone to those with mastectomy plus transverse rectus adbominis (TRAM) flap BR. Methods: The prospective cohort study included women treated with mastectomy at Women’s College Hospital from 1987 to 1997. Women with TRAM flap BR were matched to controls based on age and year of diagnosis, stage, and nodal status. Patients were followed from the date of diagnosis until death or date of last follow-up. Hazard ratios were generated to compare cases and controls for outcome variables using Cox’s proportional hazards models. Results: Of 443 women with invasive breast cancer, 85 subjects had TRAM flap BR. Sixty-five of these women were matched to 115 controls. The mean follow-up was 11.2 (0.4–26.3) years. There were no significant differences between those with and without BR with weight, height, or smoking status. Women with TRAM flap were less likely to experience a distant recurrence compared to women without a TRAM flap (relative risk, 0.42; P = 0.0009) and were more likely to be alive (relative risk, 0.54; P = 0.03). Conclusions: Women who elect for TRAM flap BR after an invasive breast cancer diagnosis do have lower rates of recurrences and mortality than women treated with mastectomy alone. This cannot be explained by differences in various clinical or lifestyle 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) | 0.001 | 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".