The impact of margin status on local recurrence following breast conserving therapy for invasive carcinoma in Manitoba
Bibliographic record
Abstract
BACKGROUND: Histologically positive margins are generally considered unacceptable with breast conserving therapy (BCT) given the increased risk of local recurrence (LR). What constitutes an adequate negative margin remains controversial. Margin status was explored as a predictor of LR post-BCT. METHODS: Manitoba women with loco-regional progression and/or mastectomy >6 months following BCT for Stage I/II invasive cancer (1995-2004) were identified from the Manitoba Cancer Registry; LR cases were confirmed by chart review. Three controls per case were matched by age, grade, stage, and adjuvant chemotherapy use. Margin status was categorized as histologically positive, < or =1 mm, < or =2 mm or >2 mm. Conditional logistic regression determined the odds ratio of LR by margin category. RESULTS: There were 50 LR cases in 3,017 patients who underwent BCT, with a median follow-up of 60 months. Wider margins were associated with a non-significant reduction in LR: >1 mm versus < or =1 mm (OR 0.69; 95% CI 0.28-1.69) and >2 mm versus < or =2 mm (OR 0.90; 95% CI 0.44-1.84). CONCLUSIONS: No clear benefit to wider histologically negative margins is demonstrated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".