HER2 Testing in a Population-Based Study of Patients With Metastatic Breast Cancer Treated With Trastuzumab
Bibliographic record
Abstract
Abstract Context. —The development of trastuzumab has led to new therapeutic strategies for patients with breast cancer. Trastuzumab has been shown to only be effective in those patients whose cancers are HER2 positive by either immunohistochemistry (IHC) or fluorescence in situ hybridization (FISH). Objective. —To determine the accuracy of HER2 testing in 2 provinces in Canada. Design. —Patients with metastatic breast cancer diagnosed between 1999 and 2002 who were HER2 positive in the local laboratories were included in this study. All cases were retested centrally, by IHC (using 4 methods) and FISH. In addition, 205 locally reported HER2-negative metastatic breast cancer cases were retested centrally. Results. —Concordance between the 505 local IHC-positive cases with central IHC testing varied between 79.3% and 89.6% depending on the IHC method and scoring method used. HER2 gene amplification by FISH was present in 86.1% of local IHC-positive cases. Concordance between the 205 local IHC-negative tumors with central testing ranged between 94.8% and 100% for IHC and was 98.5% for FISH. Conclusions. —This study demonstrated that locally reported HER2-negative results were highly accurate, but less accuracy was demonstrated with local HER2-positive results. These results emphasize the need for participation in a quality assurance program.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".