Comparative Analysis of Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer According to 2007 and 2013 American Society of Clinical Oncology/College of American Pathologists Guideline Recommendations
Bibliographic record
Abstract
Purpose To study the effect of the 2013 updates to the 2007 American Society of Clinical Oncology/College of American Pathologists recommendations for human epidermal growth factor receptor 2 (HER2) testing in breast cancer on testing patterns and interpretation in a large regional reference laboratory. Patients and Methods Patient cases with HER2 testing scores for breast biomarker evaluation were selected from our laboratory information system during two 12-month periods (2012 and 2014). The number of tests performed, type of specimens, proportion of HER2-positive and equivocal patient cases, and number of repeat tests on subsequent excisional specimens were examined and compared. Results Although the number of samples tested increased between 2012 and 2014 (2,201 v 2,558 patient cases; 2,278 v 2,659 tumors), HER2 positivity remained constant (15.7% v 15.5%, respectively). The number of repeat tests performed within 6 months more than doubled (122 [5.5%) of 2,201 v 302 [11.8%] of 2,558; P < .001), and the proportion of immunohistochemistry (IHC) 2+ tumors was significantly lower in 2014 than in 2012 (20.3% v 25.3%; P < .001). However, the proportion of patient cases with unresolved HER2 statuses (equivocal by IHC and in situ hybridization) was significantly higher in 2014 (four of 2,278 v 90 of 2,660; P < .001). Conclusion Our findings indicate that the 2013 updates to the American Society of Clinical Oncology/College of American Pathologists recommendations for HER2 testing in breast cancer did not affect the overall HER2-positivity rate or the proportion of patients eligible for HER2-targeted therapy. The proportion of tests and repeat tests performed increased, as did the number of patient cases categorized as ISH equivocal. The benefit of targeted therapy in the equivocal group is not proven, so targeted therapy should not be considered for patients in this category which should be redefined in future iterations of the recommendations.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".