Exploring Human Epidermal Growth Factor Receptor 2 (HER2)-Low Early Breast Cancer in a Moroccan Population: Clinical Characteristics and Survival Outcomes
Bibliographic record
Abstract
Breast cancers with low human epidermal growth factor receptor 2 (HER2) expression, classified as an immunohistochemistry (IHC) score of 1+ or 2+ without gene amplification, have recently drawn increased interest due to the emergence of novel anti-HER2 therapies. However, there is still debate over whether HER2-low tumors form a distinct category. This study set out to examine and compare the clinical characteristics and outcomes of early-stage breast cancer patients with HER2-zero and HER2-low expression. We reviewed medical records of stage I-III patients treated at Souss-Massa University Hospital Center in Morocco between 2016 and 2018. HER2-positive cases were excluded, leaving two comparison groups: HER2-zero and HER2-low. Using statistical methods, we assessed baseline characteristics and survival outcomes - disease-free survival (DFS) and overall survival (OS) - through Kaplan-Meier analysis, log-rank testing, and Cox regression models based on key prognostic factors like age, hormone receptor (HR) status, Ki-67 index, and lymph node involvement. Among 322 patients studied, we found 114 were HR-positive/HER2-zero, 95 HR-positive/HER2-low, 85 HR-negative/HER2-zero, and 28 HR-negative/HER2-low. Tumor size, nodal status, and histologic grade were similar across both groups. Notably, HER2-low tumors were more often HR-positive (95 (77.2) vs. 114 (57.3), p < 0.001), and HER2-zero tumors were more likely to have high Ki-67 levels (>20%) (95 (47.73) vs. 41 (33.33), p = 0.009). While certain subgroups, like HR-positive or high Ki-67 cases, showed better DFS in the HER2-low group, overall, there were no significant differences in DFS or OS. These results suggest HER2-low and HER2-zero breast cancers share largely similar features and outcomes; however, in certain subgroups, HER2-low tumors were associated with significantly better DFS, possibly reflecting differences in tumor biology. Further research is essential to clarify the biological role of HER2-low expression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".