Cardiac and Inflammation Biomarker Profile after Initiation of Adjuvant Trastuzumab Therapy
Bibliographic record
Abstract
To the Editor: Liebetrau and colleagues have reported mechanistic data indicating that cardiac biomarkers appear rapidly in the blood upon induction of myocardial cell necrosis (1). Interestingly, concentrations of cardiac troponin T (cTnT)1 in both high-sensitivity (hs-cTnT) and fourth-generation assays continue to increase up to 1 day after the onset of necrosis. These data support the argument that irreversible myocardial injury causes prolonged release of cardiac troponin into the blood. Many anticancer therapies produce myocardial injury. Accordingly, measurement of blood cardiac biomarkers 1 day after therapy initiation may be necessary to assess whether irreversible myocardial injury has occurred. That may be important in the setting of trastuzumab treatment for human epidermal growth factor receptor 2–positive breast cancers, in which data have shown that this agent may cause cardiotoxicity, specifically a decrease in the left ventricular ejection fraction, which could lead to heart failure (2). Recent data have also suggested that inflammation (as assessed by C-reactive protein measurement) might be better than cardiac troponin I (cTnI) and the natriuretic peptides as a prognostic factor for the development of trastuzumab-mediated cardiotoxicity, although the cTnI assay used in that study was not a high-sensitivity assay (2). Moreover, earlier and additional inflammation biomarkers (as opposed to C-reactive protein) have also been demonstrated to identify the patients …
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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 | 0.001 | 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 | 0.002 | 0.002 |
| 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 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".