Evaluation, prevention and management of cancer therapy-induced cardiotoxicity
Bibliographic record
Abstract
PURPOSE OF REVIEW: While targeted therapies have improved cancer outcomes, unique cardiovascular toxicities are increasingly recognized, particularly when administered sequentially after anthracyclines or radiation. Patients with cancer therapy-induced cardiotoxicity benefit from collaborative care involving cardiology and oncology, leading to a new interdisciplinary field called cardio-oncology. The present review will highlight contemporary clinical issues in cardio-oncology. RECENT FINDINGS: Recently, risk factors for cancer therapy-induced cardiotoxicity have been evaluated in real-world rather than in clinical trial patients. Biomarkers and advanced echocardiography are emerging as sensitive tools for preclinical identification of cancer therapy-induced cardiotoxicity. Single-center studies suggest that cancer therapy-induced cardiotoxicity responds to prompt heart failure medical treatment, and such therapy may even prevent cardiotoxicity. SUMMARY: Modern cancer therapy has short-term cardiac risk that may require collaborative management by clinicians with expertise in cardiology and oncology. The increased effectiveness of modern cancer therapy is resulting in a growing population of cancer survivors who are at long-term risk for cardiovascular disease. The present review of contemporary clinical issues in cardio-oncology will be of interest to healthcare providers who manage cardiotoxicity during cancer therapy, and who follow patients who survive cancer but face increased long-term cardiovascular risk.
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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) | 0.000 | 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".