Acute Adverse Effects of Radiation Therapy and Local Recurrence in Relation to Dietary and Plasma Beta Carotene and Alpha Tocopherol in Head and Neck Cancer Patients
Bibliographic record
Abstract
There is a debate concerning the effects of antioxidant vitamins during radiation therapy: Can they reduce the adverse effects of therapy without reducing treatment efficacy? We examined whether dietary and plasma beta carotene and alpha tocopherol were related to severe acute adverse effects of radiation therapy and to cancer local recurrence. We conducted a prospective study of 540 head and neck cancer patients treated by radiation therapy. Dietary intakes of beta carotene and alpha tocopherol were measured by a validated food frequency questionnaire and plasma levels were determined. Acute adverse effects of radiation therapy and local recurrence were documented. A higher beta carotene dietary intake was associated with fewer severe acute adverse effects: odds ratio (OR) = 0.61 [95% confidence interval (CI) = 0.40-0.93]. There was a tendency for a similar effect for plasma beta carotene: OR = 0.73 (95% CI = 0.48-1.11). Participants with higher plasma beta carotene had a significantly lower rate of local recurrence (hazard ratio = 0.67; 95% CI = 0.45-0.99). Alpha tocopherol was not related to severe adverse effects or to cancer recurrence. This study suggests that a higher usual dietary beta carotene intake can reduce the occurrence of severe adverse effects of radiation therapy and decrease local cancer recurrence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".