Antioxidant Food Supplementation in Cancer: Lessons from Clinical Trials and Insights from Preclinical Studies
Bibliographic record
Abstract
Food antioxidant supplementation has been widely proposed for cancer prevention and adjuvant therapy due to the pleiotropic role of antioxidants. Herein, particular attention is given to recent clinical trials based on the use of dietary supplements in cancer patients, both as monotherapy and in combination with standard treatments, exploring both their potential benefits and risks. This review focuses on the efficacy of the most important food antioxidants, highlighting how their action may change depending on different factors such as cancer type, dose, timing of administration and antioxidant status of the patient. The results of clinical trials are often contradictory, and the clinical benefit of dietary antioxidants appears more consistent in patients with a baseline antioxidant deficiency. Furthermore, by analyzing the mechanisms underlying the contradictory clinical evidence and critically addressing the issues related to the methodologies used in preclinical models, this review could be helpful in guiding the personalized use of antioxidant supplementation in cancer patients.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".