Comparison of Recurrence and Survival Rates after Breast-Conserving Therapy and Mastectomy in Young Women with Breast Cancer
Bibliographic record
Abstract
Multiple randomized trials have demonstrated that breast-conserving therapy with partial mastectomy and radiotherapy provides survival equivalent to that seen with mastectomy for patients with early-stage breast cancer. Breast-conserving therapy has been associated with better quality of life relative to mastectomy and has become the standard of care for patients with early-stage breast cancer. Young age has been identified as a risk factor for recurrence and death from breast cancer. Some studies have suggested that young women (less than 35 or 40 years of age) have inferior outcomes with breast-conserving therapy, implying that such women may be better served by mastectomy. On review of the available literature, there is no definitive evidence that mastectomy provides a consistent, unequivocal recurrence-free or overall survival benefit over breast-conserving therapy. However, available meta-analyses have not compared outcomes in young women specifically, and such analyses should be performed. In the interim, breast-conserving therapy is not contraindicated in young women (less than 40 years of age) and can be used cautiously; however, such women should be advised of the lack of unequivocal data proving that survival is equivalent to that with mastectomy in their age group.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".