Challenges & recommendations for identification of human epidermal growth factor receptor -2 (HER2)-low metastatic breast cancer in India: Expert opinion statement
Bibliographic record
Abstract
Results from a recent Phase 3 clinical trial (DESTINY-Breast04) established the efficacy of the antibody-drug conjugate, trastuzumab deruxtecan (T-DXd) in patients with metastatic breast cancer with immunohistochemistry (IHC) score 1+ or 2+ and without in situ hybridization amplification, defining a new category of metastatic breast cancer known as human epidermal growth factor receptor 2 (HER2)-low. Across studies of patients with primary or metastatic breast cancer, approximately 50 per cent have HER2-low tumours, thereby emphasizing the importance of accurately identifying these tumours. Results from the DESTINY-Breast06 trial further corroborated the DESTINY-Breast04 results showing T-DXd as a new standard of care for patients with HER2-low and HER2-ultralow (defined as IHC score 0 with membrane staining) metastatic breast cancer following one or more lines of hormone therapy. Differentiating between HER2 IHC scores 0 and 1+ shows significant interobserver variability, possibly because the low scores did not have any clinical relevance until now. To establish a standardized approach in scoring of HER2-low tumours in India, a panel of experts comprising histopathologists, molecular pathologists, and clinicians met to discuss guidelines on HER2 testing. The identification of HER2-low expression depends on multiple methodological pre-analytical and analytical variables, including sample handling, fixation, processing, antigen clones, staining methodology, and substrates. The panel also focused on the challenges in the interpretation of HER2-low status. Challenges in the pre-analytical and analytical phases could be addressed by rigorous quality control procedures and training the pathologists. In the post-analytical phase, the subjective mode of HER2 assessment and HER2 intratumoural heterogeneity in HER2-low breast cancer are factors that influence HER2-low assessment. The panel recommended robust standard operating procedures to overcome these challenges. The central point of discussion was to implement clear guidelines, careful supervision of pre-analytical and analytical issues, and specialized training for accurate HER2 testing that would help select patients eligible for novel therapies.
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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 | 0.025 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".