Outcomes of her2-positive Early-Stage Breast Cancer in the Trastuzumab Era: A Population-Based Study of Canadian Patients
Bibliographic record
Abstract
UNLABELLED: Breast cancer is heterogenous, with variable expression of the estrogen receptor (er), progesterone receptor (pr), and human epidermal growth factor receptor 2 (her2). Overexpression of her2 is generally considered a negative prognostic feature, but whether outcomes for her2-positive early breast cancer remain different from those for other subtypes in the era of trastuzumab-based adjuvant therapy is unknown. METHODS: Using a retrospective chart review, we compared overall survival (os) and relapse-free survival (rfs) in 3 groups of patients with early-stage breast cancer: er-positive or pr-positive (or both) and her2-negative ["hormone receptor-positive" (hr+)]; her2-positive (her2+); and er-negative, pr-negative, and her2-negative ["triple-negative" (tn)]. RESULTS: In the 503 charts analyzed (332 hr+, 94 her2+, 77 tn), the 5-year os and rfs were, respectively, 94.2% and 87.2% for hr+ patients, 88.6% and 74.9% for her2+ patients, and 85.4% and 76.2% for tn patients. On multivariate analysis, the os for the her2+ subtype was similar to that for the hr+ subtype (hazard ratio:1.07; 95% confidence interval: 0.31 to 3.67 with hr+ as reference), but os was significantly worse for tn patients than for hr+ patients (hazard ratio: 4.37; 95% confidence interval: 1.56 to 12.24). In her2+ patients, the 5-year os and rfs trended better for patients with er+ or pr+ disease than for patients with er-negative and pr-negative disease (5-year os: 92.1% vs. 86.9%; 5-year rfs: 79.8% vs. 71.4%). Of her2+ patients, just 80.9% received trastuzumab, including 33.3% of her2+ patients with sub-centimetre tumours. CONCLUSIONS: In the trastuzumab era, patients with her2+ and hr+ early breast cancer have similar outcomes, while tn patients experience a significantly worse os than either of the foregoing groups. Outcomes for her2+ patients may differ by er and pr status. Trastuzumab was underutilized in this cohort.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".