Management of radial scars found at percutaneous breast biopsy.
Bibliographic record
Abstract
OBJECTIVE: To determine whether percutaneous biopsy can safely differentiate radial scars (RS) that can be followed from those that require excision. METHODS: Retrospective analysis of prospectively collected data regarding 15 986 biopsies was performed at the Centre Hospitalier de l'Université de Montreal between October 1995 and December 2003 and yielded 227 RS. The type of biopsy, number of cores, and mammographic characteristics were recorded. Only lesions with surgical pathology or 24 months of mammographic stability were considered for analysis. Subgroup analyses were performed for patients who underwent 14-gauge core biopsy (CB), 11-gauge vacuum-assisted biopsy (VAB), or both. RESULTS: Among the 14-gauge CBs (n = 176), data were available for 144 (81.8%); among the 11-gauge VABs (n = 51), data were available for 40 (78.4%). Thirty lesions had 14-gauge CB followed by 11-gauge VAB. RS were associated with cancer in 19.6%, with a high-risk lesion in 20.1% and a benign lesion in 60.3%. Overall, 4% of cancers were missed (5% for 14-gauge CB and 0% for 11-gauge VAB), and cancer was underestimated in 22.2% (25% for 14-gauge CB and 16.7% for 11-gauge VAB). One (3.7%) additional cancer was found when benign radial scar on 14-gauge CB underwent subsequent 11-gauge VAB. Cancer was associated with 37% of RS presenting as masses but with only 17.1% of distortions and 12.3% of microcalcifications. CONCLUSIONS: If benign radial scar is found on 14-gauge CB, further evaluation is needed with 11-gauge VAB or surgery. Our data support mammographic follow-up for RS that are benign on 11-gauge VAB.
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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".