TITAN Trial
Bibliographic record
Abstract
Cardiac rehabilitation (CR) modeled care is recommended for patients with breast cancer to mitigate risk of cardiotoxicity. However, the cardiovascular impact of CR-modeled interventions has not been studied. The purpose of this study was to evaluate if a multidisciplinary model of CR reduces cardiotoxicity and improves cardiovascular risk in patients undergoing breast cancer treatment. We randomly assigned patients with stage I to III breast cancer scheduled to receive anthracycline and/or trastuzumab-based chemotherapy to the CR intervention (n = 37) or usual care (n = 37). The intervention included guideline-directed management of cardiovascular risk factors, dietary counselling, and supervised exercise for 52 weeks. Cardiac magnetic resonance imaging, cardiopulmonary exercise testing, dual-energy x-ray absorptiometry, and serum biomarkers were acquired at baseline and 52 weeks. There was no difference in the primary outcome, left ventricular ejection fraction (LVEF), between groups at 52 weeks (61% ± 6%). Other markers of cardiotoxicity, including high-sensitivity troponin I and brain natriuretic peptide, were similar between groups. However, total cholesterol (5.2 ± 0.8-4.7 ± 0.8 mmol/L, P = 0.002) and low-density lipoprotein (3.0 ± 0.7-2.4 ± 0.7 mmol/L, P < 0.001) decreased in the intervention group at 52 weeks and were unchanged in usual care. In all patients, adverse cardiac and metabolic changes occurred over 52 weeks including reductions in LVEF, left ventricular mass, high-density lipoprotein, lean body mass, insulin-like growth factor-1, as well as increased triglycerides, whole-body and truncal fat mass (all P < 0.050). The CR-modeled intervention had no effect on LVEF or biomarkers of cardiotoxicity. Future lifestyle intervention trials in patients with breast cancer should consider targeting other risk factors associated with incident cardiovascular disease. (Multidisciplinary Team IntervenTion in CArdio-ONcology [TITAN Study] [TITAN]; NCT01621659)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.063 | 0.012 |
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".