N − 3 fatty acids during chemotherapy: toward a higher level of evidence for clinical application
Bibliographic record
Abstract
PURPOSE OF REVIEW: Recommendations for intakes of n - 3 fatty acids (FAs) in patients who are receiving chemotherapy for cancer are based on weak evidence. This review highlights themes within the emergent literature to suggest improvements in the design of studies that provide n - 3 FA supplements concurrent with cytotoxic agents. RECENT FINDINGS: Following earlier research in animal models and human pilot studies, recent human studies have evaluated the effect of providing n - 3 FAs during delivery of single agent and multiagent chemotherapy regimens for breast and gastro-intestinal cancers. Regimens were based on platinum compounds, fluoropyrimidines or both, and a variety of additional agents. Tumor location and stage, supplement dose and duration, and endpoints were dissimilar across studies. Overall, the recent research continues to support the safety and tolerability of n - 3 FA supplementation with chemotherapy and provides additional evidence, albeit weak, for enhanced tumor response, maintenance of weight and muscle, and reduction in inflammation and toxicities in the host across multiple cancer sites and chemotherapy regimens. SUMMARY: The barriers to implementation in practice remain small study sizes, variations in supplement dosage and methodology, and differences in primary endpoints. Randomized, blinded trials with a justifiable sample size, adequate doses, monitored compliance and measures of clinically important endpoints are required to move these findings to a higher level of evidence for implementation into clinical practice.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".