Mammary Spindle Cell Proliferations on Core Needle Biopsy
Bibliographic record
Abstract
Mammary spindle cell proliferations (SCPs) encompass a wide range of lesions and can be challenging to accurately diagnose on core needle biopsies (CNBs). Most SCPs are excised for definitive diagnosis. In the era of minimally invasive therapy, some SCP may be followed conservatively. We aim to examine the spectrum of SCP diagnosed on CNB and evaluate if excision of benign/indeterminate SCP is always required. We identified patients with SCP across 3 institutions. The CNB were classified into benign, indeterminate, or malignant. Available excisional specimens were used to classify the lesion as benign or malignant. Clinical variables were reviewed. A total of 197 SCP met the inclusion criteria, including 100 (53%) CNB classified as benign, 52 (26%) indeterminate, and 36 (19%) malignant. Nine patients had excisions without a preceding CNB. Excision was performed in 47% of benign, 87% of indeterminate, and 86% malignant CNB. Of 123 excised SCP, 77 (63%) were benign, while 44 (36%) were malignant. Most benign lesions were not suspicious radiologically (67%), while indeterminate and malignant lesions were more likely to be suspicious (44% and 75%, respectively; P <0.001). Malignant lesions tended to present as larger, rapidly growing, masses. Most mammary SCP are benign (63% of excisions). Appropriate ancillary tests can safely exclude some malignant entities. We encourage narrowing down the differential diagnosis to pertinent entities based on clinical presentation, imaging, histology, immunohistochemistry, and molecular studies, if applicable. Patients with mammary SCP may be spared surgery provided accurate pathologic diagnosis and appropriate correlation with imaging and clinical data.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".