Trastuzumab-related subclinical cardiotoxicity in patients with early stage HER2-positive breast cancer: A retrospective single-center cohort study.
Bibliographic record
Abstract
10123 Background: Trastuzumab-based therapy (TT) is standard treatment for HER2-positive breast cancer (HBC). Subclinical cardiotoxicity (SCTx), defined as asymptomatic decline in left ventricular ejection fraction (LVEF) > 10% to < 50%, has been reported in up to 30 % of HBC patients (pts) receiving TT. Objectives included: determine prevalence of SCTx; associated risk factors (RF); and completion rates of TT in pts with HBC referred to a cardio-oncology clinic (COC). Methods: HBC patients receiving TT referred to the Ottawa Hospital COC were included. Demographics, TNM staging, performance status, stage, cardio-vascular (CV) RF (history of heart disease, hypertension, smoking, dyslipidemia, and diabetes), cardiac medications (CM) (ACE-inhibitors, beta-blockers), baseline LVEF, previous cancer therapy, baseline anthracycline exposure, previous radiation therapy (RT) (including mediastinal RT) were collected. LVEF was evaluated by ECHO or MUGA. Rate of successful completion of TT among pts with SCTx was determined. Risk ratio (RR) and logistic regression analysis was performed. Results: 240/408 BC pts referred to the COC (2008-2016) had HBC and 163/240 (68%) were referred with SCTx while on TT. 139/163 (85 %) pts with SCTx recovered after COC assessment: 77/163 (47%) pts were prescribed CMs. A significantly higher proportion of recovery was observed in pts who did not require CM (0.92 vs 0.78, p = 0.012; RR = 0.85, 95%CI:0.74-0.91). A total of 129/163 (79%) pts who experienced SCTx finished a full course of TT. Regression analysis found baseline LVEF, diabetes, and diastolic blood pressure as significant RFs for SCTx. There were no independent predictors for recovery after asymptomatic drop in LVEF while on TT. Diabetes (OR:2.97, 95%CI:1.3-6.8) and left chest wall RT (OR:2.4, 95%CI:1.1-5.6) significantly increased risk of permanent TT interruption in pts with asymptomatic drop in LVEF. Conclusions: The majority of HBC pts who experience SCTx can safely complete a full course of TT; many without use of CMs. While CV RFs were associated with increased risk of SCTx, this did not impact CV recovery after asymptomatic drops in LVEF.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".