Cytokeratin 5 and Estrogen Receptor Immunohistochemistry as a Useful Adjunct in Identifying Atypical Papillary Lesions on Breast Needle Core Biopsy
Bibliographic record
Abstract
The presence of atypical or usual epithelial proliferations within papillary breast lesions complicates their interpretation on core biopsy. We evaluated the combination of estrogen receptor (ER) and cytokeratin 5 (CK5) as an aid in the distinction of usual duct hyperplasia from atypical proliferations in this setting. Core biopsies from 185 papillary lesions were reviewed and of these, 82 cases were selected for immunohistochemical study based on the presence of an epithelial proliferation between the fibrovascular cores. Fifty-two cases were used as the test set and 30 cases, with subsequent surgical excision, were used as the validation set. The epithelial proliferation was evaluated for staining intensity and percentage of positive cells using CK5 and ER. Expression of both CK5 and ER was significantly different in nonatypical lesions when compared with atypical lesions (P<0.0001). Nonatypical lesions typically showed an ER-low/CK5-high profile and atypical lesions showed an ER-high/CK5-low profile with ER-high expression defined as diffuse strong staining in >90% of cells. CK5-high expression was defined as a mosaic pattern of staining in >20% of cells and CK5-low as absent or staining in <20% of cells. On the basis of their staining profile, 29 of the 30 validation cases were correctly classified using the excision specimen as the gold standard. Patterns and extent of ER and CK5 staining, when used together, are valuable adjunct stains to differentiate usual duct hyperplasia from atypical proliferations within papillary lesions on core biopsy.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".