The impact of mild left ventricular dysfunction on trastuzumab use and oncologic outcomes in early stage breast cancer therapy.
Bibliographic record
Abstract
e18148 Background: Trastuzumab (T) significantly reduces the risk of breast cancer recurrence, but may be associated with an increased incidence of heart failure. The intention of this study was to assess how T therapy was managed after the development of mild left ventricular ejection fraction (LVEF) drop in a non-trial setting and to evaluate the cardiovascular and oncologic outcomes. Methods: Patients (pts) who received adjuvant T therapy in British Columbia for breast cancer between September 2005 and December 2013 were identified. Pts were eligible if they had a drop in LVEF to 40-49% after starting T. Charts were reviewed for demographic information. Pts were divided into 2 cohorts: those who continued T without interruption, and those who had any interruption or discontinuation. Breast cancer outcomes and cardiac outcomes were compared in each of these groups. Results: Of the 2401 pts who were screened, 261 (10.9%) pts had a drop in LVEF to 40-49%. Of these, 229 (87.7%) had an interruption in T, while 32 (12.3%) did not have an interruption in therapy. The number of pts who experienced a cancer relapse in the T interruption and continuous groups were 38 (16.6%) and 2 (6.25%), respectively (P = 0.19). Even amongst those who received a full 17 cycles of therapy, there was a 11.25% absolute increase in the risk of breast cancer recurrence (17.5% vs 6.25%) in those who had an interruption in their course of treatment compared to those who did not have an interruption (p = 0.15). Cardiac outcomes (subsequent LVEF drop < 40% or CHF) were higher in the group of pts who had treatment interrupted compared to those who had continuation of T (14.8% vs 0%). Conclusions: Interrupting T after the development of mild left ventricular dysfunction was associated with a 10.35% (p = 0.19) absolute increase in breast cancer recurrence. Continuing T was not associated with an increased risk of long term cardiovascular events. While these results are not statistically significant, they are concerning and warrant further investigation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".