Practical Considerations in Breast Papillary Lesions: A Review of the Literature
Bibliographic record
Abstract
CONTEXT: -Diagnosis of papillary breast lesions, especially in core biopsies, is challenging for most pathologists, and these lesions pose problems for patient management. Distinction between benign, premalignant, and malignant components of papillary lesions is challenging, and the diagnosis of invasion is problematic in lesions that have circumscribed margins. Obtaining a balance between overtreatment and undertreatment of these lesions is also challenging. OBJECTIVES: -To provide a classification and a description of the histologic and immunohistochemical features and the differential diagnosis of papillary breast lesions, to provide an update on the molecular pathology of papillary breast lesions, and to discuss the recommendations for further investigation and management of papillary breast lesions. This review provides a concise description of the histologic and immunohistochemical features of the different papillary lesions of the breast. DATA SOURCES: -The standard pathology text books on breast pathology and literature on papillary breast lesions were reviewed with the assistance of the PubMed database ( http://www.ncbi.nlm.nih.gov/pubmed ). CONCLUSIONS: -Knowledge of the clinical presentation, histology, immunoprofile, and behavior of papillary breast lesions will assist pathologists with the diagnosis and optimal management of patients with papillary breast lesions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".