Complete Surgical Excision Is Necessary following Vacuum-Assisted Biopsy for Breast Cancer
Bibliographic record
Abstract
Vacuum-assisted breast biopsy (VABB) has been replacing excisional biopsy in the treatment of benign breast lesions. Complete surgical excision is still needed for the lesions occasionally diagnosed with breast cancer after VABB. We aimed to characterize residual tumors after VABB and define a subset of patients who do not need surgical excision after VABB. From a retrospective database, we identified patients diagnosed with breast cancer after VABB guided with ultrasonography. Patients who underwent stereotactic biopsies were excluded. We reviewed clinicopathologic data and radiologic findings of the sample. We identified 48 patients with 49 lesions. After surgical excision, the residual tumors were identified in 40 (81.6%) lesions, and there was no residual tumor in nine (18.3%) patients. Imaging studies could not accurately locate residual tumors after VABB. A small tumor size on a VABB specimen was associated with no residual tumor on final pathology. However, residual tumors were identified in four (40%) of 10 lesions with a pathologic tumor size less than 0.5 cm. In conclusion, complete surgical excision remains the primary option for most of the patients diagnosed with breast cancer after VABB. Imaging surveillance without surgery should be carefully applied for selected low-risk 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.001 |
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".