HER2DX ERBB2 mRNA expression in advanced HER2-positive breast cancer treated with T-DM1
Bibliographic record
Abstract
In advanced HER2-positive (HER2+) breast cancer, the new antibody-drug conjugate trastuzumab deruxtecan is more effective compared with trastuzumab emtansine (T-DM1). However, trastuzumab deruxtecan can have considerable toxicities, and the right treatment sequence is unknown. Biomarkers to guide the use of anti-HER2 therapies beyond HER2 status are needed. Here, we evaluated if preestablished levels of ERBB2 mRNA expression according to the HER2DX standardized assay are associated with response and survival following T-DM1. In ERBB2 low, medium, and high groups, the overall response rate was 0%, 29%, and 56%, respectively (P < .001). ERBB2 mRNA was statistically significantly associated with better progression-free survival (P = .002) and overall survival (OS; P = .02). These findings were independent of HER2 immunohistochemistry (IHC) levels, hormone receptor, age, brain metastasis, and line of therapy. The HER2DX risk score (P = .04) and immunoglobulin signature (P = .04) were statistically significantly associated with overall survival since diagnosis. HER2DX provides prognostic and predictive information following T-DM1 in advanced HER2+ breast cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".