Impact of Stopping Trastuzumab in Early Breast Cancer: A Population-Based Study in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Adjuvant trastuzumab for early-stage (I-III) HER2-positive breast cancer (BC) has led to statistically significant improvement in cancer outcomes but carries a risk of cardiotoxicity. Trastuzumab is discontinued early in many patients for asymptomatic changes in left ventricular ejection fraction. We evaluated the impact of early discontinuation of trastuzumab on cancer outcomes. METHODS: We conducted a retrospective population-based cohort study of early BC patients treated with adjuvant trastuzumab in Ontario, Canada, 2007-2016. Four groups were analyzed: group A was full treatment, 17-18 cycles trastuzumab; group B was cardiac event (CE) within treatment period; group C was ≤16 cycles, no CEs, stopped within 30 days from last cardiac imaging; and group D was ≤16 cycles, no CEs, stopped more than 30 days from cardiac imaging. Primary outcome was disease-free survival (DFS); secondary outcomes were: overall survival, cancer-specific mortality, and cardiovascular mortality. Sensitivity analyses were performed 14 months after cycle 1 trastuzumab to control for early relapse. RESULTS: A total of 5547 patients met the inclusion criteria: group A = 3921, group B = 309, group C = 362, and group D = 955. The 5-year DFS was 94.1% in group A, 80.1% in group B, 81.4% in group C, and 82.4% in group D. Using a Cox model, the hazard ratio for 5-year DFS was 3.15 (95% confidence interval [CI] = 2.13 to 4.65) for group B, 1.94 (95% CI = 1.30 to 2.89) for group C, and 1.92 (95% CI = 1.46 to 2.53) for group D. Overall, 26 patients (0.5%) died of cardiac causes. CONCLUSIONS: BC patients in Ontario who did not complete adjuvant trastuzumab had a statistically significantly higher risk of BC relapse and death and low incidence of cardiac death. These findings support 1 year of adjuvant trastuzumab in early-stage BC.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".