Characteristics and Outcomes of Women Developing Heart Failure After Early Stage Breast Cancer Chemotherapy: A Population-Based Matched Cohort Study
Bibliographic record
Abstract
Background: The prognosis of heart failure (HF) after early stage breast cancer (EBC) treatment with anthracyclines or trastuzumab is not well-characterized. Methods: Using administrative databases, women diagnosed with HF after receiving anthracyclines or trastuzumab for EBC in Ontario during 2007 to 2017 (the EBC-HF cohort) were categorized by cardiotoxic exposure (anthracycline alone, trastuzumab alone, sequential therapy with both agents) and matched on age with ≤3 cancer-free HF controls to compare baseline characteristics. To study prognosis after HF onset, we conducted a second match on age plus important HF prognostic factors. The cumulative incidence function was used to describe risk of hospitalization or emergency department visits (hospital presentations) for HF and cardiovascular death. Results: A total of 804 women with EBC developed HF after anthracyclines (n=312), trastuzumab (n=112), or sequential therapy (n=380); they had significantly fewer comorbidities than 2411 age-matched HF controls. After the second match, the anthracycline-HF cohort had a similar 5-year incidence of HF hospital presentations (16.5% [95% CI, 12.0%–21.7%]) as controls (17.1% [95% CI, 14.4%–20.1%]); the 5-year incidence was lower than matched controls for the trastuzumab-HF (9.7% [95% CI, 4.7%–16.9%]; controls 16.4% [95% CI, 12.1%–21.3%]; P =0.03) and sequential-HF cohorts (2.7% [95% CI, 1.4%–4.8%]; controls 10.8% [95% CI, 8.9%–13.0%]; P <0.001). At 5 years, the incidence of cardiovascular death was 2.9% (95% CI, 1.2%–5.9%) in the anthracycline-HF cohort vs. 9.5% (95% CI, 6.9%–12.6%) in controls, and 1.7% (0.6%–3.7%) for women developing HF after trastuzumab vs. 4.3% (95% CI, 3.1–5.8%) for controls. Conclusions: Women developing HF after cardiotoxic EBC chemotherapy have fewer comorbidities than cancer-free women with HF; trastuzumab-treated women who develop HF have better prognosis than matched HF controls.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".