Long-term risk of heart failure associated with adjuvant trastuzumab in breast cancer patients.
Bibliographic record
Abstract
9504 Background: The late cardiac effect of adjuvant trastuzumab (T) and its potential interaction with anthracycline in the general population have not been well studied. The purpose of this retrospective population-based cohort study was to determine the long-term risk of heart failure (HF) associated with adjuvant T and chemotherapy, compared to chemotherapy alone. Methods: Female breast cancer patients in Ontario, diagnosed between 2003 and 2009 were identified by the Ontario Cancer Registry and linked to administrative databases to ascertain demographics, cardiac risk factors, comorbidities, and use of adjuvant T and other chemotherapy. Patients with pre-existing HF were excluded. The main endpoint was new diagnosis of HF, obtained using an algorithm of admission and physician claims data. Group differences were assessed by the Kaplan-Meier (KM) method and multivariable piecewise Cox regression. Competing risk analysis using the Fine and Gray method and propensity score matching analysis were performed. Results: 19,074 women with breast cancer treated with adjuvant chemotherapy were identified, of whom 3 371 (17.7%) also received adjuvant T. Anthracycline use was 84.9% overall. The groups did not differ significantly in demographics, comorbidities, or cardiac risk factors. After a median follow-up of 5.9 years, patients treated with T and chemotherapy were more likely to develop HF than patients on chemotherapy alone (5-year KM estimates of 5.3% vs. 2.6%; p<0.0001 (log-rank)). After adjusting for confounders, adjuvant T remained independently associated with incident HF in the first 1.5 years (HR=5.77, 95% CI 4.38-7.62, p=0.0004), but not thereafter (HR=0.87, 95% CI 0.57-1.33, p=0.53). Anthracycline did not increase the risk of HF with T synergistically (interaction p=0.23). Competing risk and propensity score analyses revealed similar results. Conclusions: In this large population-based cohort study of breast cancer patients with long-term follow-up, adjuvant T was associated with increased risk of HF in breast cancer survivors, within the first 1.5 years of initiating treatment, but not thereafter. This provides reassurance about the long-term cardiac safety of adjuvant T in the general population.
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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 | 0.000 |
| 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 | 0.000 |
| 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".