Effects of omega-3 fatty acids supplementation on neoadjuvant chemotherapy-induced toxicity in patients with locally advanced breast cancer: a randomized, controlled, double-blinded clinical trial
Bibliographic record
Abstract
INTRODUCTION: Background: antineoplastic treatment for locally advanced breast cancer (LABC) includes neodjuvant chemotherapy (NeoCT). However, side effects occur frequently, affecting the functional capacity and quality of life of patients as a result of the proinflammatory state of this therapy. In this work, omega-3 polyunsaturated fatty acids (PUFA Ω-3) were administered as they have been reported to modulate some molecular pathways such as nuclear factor-kappa B (NF-κB), which is associated with toxicity secondary to the administration of anthracyclines. Objective: to evaluate the effects of PUFA Ω-3 on the toxicity, side effects, body composition, cardiometabolic profile and quality of life in women with LABC after NeoCT. Methods: fifty-three women with LABC were included in a double-blinded, placebo-controlled clinical trial. Patients randomly received 2.4 g/day of PUFA Ω-3 (EPA 1.6 g and DHA 0.8 g) or placebo during NeoCT with adriamycin/cyclophosphamide followed by paclitaxel+/-trastuzumab. Adverse effects related to chemotherapy were evaluated using the Common Terminology Criteria for Adverse Events (CTCAE, version 4.03) and the Subjective Global Scale of the Edmonton Symptom Assessment System (ESAS). Body composition and cardiometabolic blood profile were also evaluated. Results: no significant differences were found between groups in the hematological and anthropometric toxicity parameters. Within the Edmonton scale, xerostomia presented a significant improvement (p = 0.032) in patients supplemented with PUFA Ω-3. Conclusion: supplementation with PUFA Ω-3 showed no change in body composition, cardiometabolic profile or toxicity due to NeoCT. It only showed significant improvement in xerostomia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".