Shorter Durations of Anti-HER2 Therapy for Patients with Early-Stage, HER2-Positive Breast Cancer: The Physician Perspective
Bibliographic record
Abstract
Despite evidence from clinical trials showing the efficacy of shorter durations of therapy, most HER2-positive early breast cancer (EBC) patients receive a year of anti-HER2 therapy. A survey of Canadian oncologists was conducted online, with electronic data collection, and the analysis is reported descriptively. Measures collected included current practices with respect to the duration of adjuvant anti-HER2 therapy, perspectives on data regarding shorter durations of treatment, and interest in further trials on this subject. Responses were received from 42 providers across Canada. Half (50%, 21/42) reported having never recommended 6 months of anti-HER2 therapy. The primary reason physicians consider a shorter duration is in response to treatment-related toxicities (76%, 31/41). Most participants (79%, 33/42) expressed the need for more data to determine which patients can be safely and effectively treated with shorter durations. Patient factors such as young age, initial stage, hormone receptor status, and type of neoadjuvant chemotherapy were attributed to reluctance to offer shorter durations of treatment. Many respondents (83%, 35/42) expressed interest in participating in the proposed clinical trial of 6 months of anti-HER2 therapy. In contemporary Canadian practice, 12 months of anti-HER2 therapy remains the primary practice. Future trials are required to better define the role of shorter treatment durations.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".