Well‐differentiated invasive breast cancers with equivocal <scp>HER</scp>2 immunohistochemistry: what is the yield of routine reflex <i>in‐situ</i> hybridization testing?
Bibliographic record
Abstract
AIMS: The 2013 American Society of Clinical Oncology and the College of American Pathologists (ASCO/CAP) HER2 guidelines recommend testing all invasive breast cancers for HER2, typically with immunohistochemistry (IHC) followed by in-situ hybridization (ISH) when IHC is equivocal. As well-differentiated breast cancers are rarely HER2-positive, we assessed the value of routine reflex HER2 ISH testing for this subset of breast cancers. METHODS AND RESULTS: We collected HER2 IHC 2+ cases and fluorescence in-situ hybridization (FISH) data from primary breast cancers with well-differentiated tumour types (grade 1 ductal carcinomas, classic lobular carcinomas, tubular, cribriform and pure mucinous carcinomas) at our centre from 2010 to 2015. Haematoxylin and eosin (H&E) and IHC slides were reviewed to confirm tumour type, grade and IHC score based on ASCO/CAP 2013 guidelines and their recent revisions. Of 4633 invasive carcinomas, 1133 had a well-differentiated tumour type; 177 of these were HER2 IHC equivocal, three of which were low-level amplified by FISH (0.3% of all well-differentiated tumours). One amplified case was classic invasive lobular carcinoma and two were invasive ductal carcinomas, grade 1. One amplified case had chromosome 17 monosomy, and one was rescored as HER2 IHC 1+ upon review. 'Basolateral' staining was noted in one amplified case and in 65 of 174 (37.4%) non-amplified cases. This incomplete membranous staining pattern was observed in the majority of invasive ductal carcinomas that were rescored as 1+ according to the revised 2013 guidelines. CONCLUSIONS: The rate of HER2 amplification among well-differentiated breast cancers is very low. Basolateral staining in well-differentiated tumours may be overinterpreted as HER2 IHC 2+, but is rarely associated with HER2 amplification.
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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 | 0.009 | 0.036 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".