Risk Factors for Anthracycline-Induced Cardiotoxicity in Breast Cancer Treatment: A Meta-Analysis
Bibliographic record
Abstract
Background Anthracyclines play an important role in the treatment of breast cancer (BC) and other malignant tumors. However, accompanied side-effects are non-ignorable. The purpose of this meta-analysis is to determine the risk factors for anthracycline-induced cardiotoxicity (ACT), so as to identify high-risk patients. Methods The search for literature was conducted in PubMed, The Cochrane Library, Embase and Web of science. Records were selected with inclusion criteria and exclusion criteria. The newcastle-ottawa scale (NOS) was used to assess the quality of literature, and Review Manager 5.3 software was used for meta-analysis. Results Thirteen studies met the inclusion criteria. Meta-analysis indicated that risk factors for ACT were use of trastuzumab (odds ratio [OR]: 2.84, 95% confidence interval [CI]: 2.49-3.22, p < 0.00001), cumulative dose of anthracyclines (OR: 1.45, 95%CI: 1.28-1.65, p < 0.00001), hypertension (OR: 2.95, 95%CI: 1.75-4.97, p < 0.0001), diabetes mellitus (DM) (OR: 1.39, 95%CI: 1.20-1.61, p < 0.0001), tumor metastasis (OR: 1.91, 95%CI: 1.17-3.11, p = 0.009) and coronary heart disease (CAD) (OR: 2.17, 95%CI: 1.50-3.15, p < 0.0001). In addition, our analysis revealed that body mass index (BMI) had no effect on ACT (OR: 1.18, 95%CI: 0.98-1.43, p = 0.08). Conclusions Patients with high risk for ACT can be identified by these factors. For such patients, a higher level of monitoring and protection for the cardiac function should be performed by clinicians. Systematic Review Registration INPLASY, identifier INPLASY202250140.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".