Sex Differences in the Effect of Vitamin D on Fatigue in Palliative Cancer Care—A Post Hoc Analysis of the Randomized, Controlled Trial ‘Palliative-D’
Bibliographic record
Abstract
In the randomized, placebo-controlled, double-blind trial ‘Palliative-D’, vitamin D treatment of 4000 IE/day for 12 weeks reduced opioid use and fatigue in vitamin-D-deficient cancer patients. In screening data from this trial, lower levels of vitamin D were associated with more fatigue in men but not in women. The aim of the present study was to investigate possible sex differences in the effect of vitamin D in patients with advanced cancer, with a specific focus on fatigue. A post hoc analysis of sex differences in patients completing the Palliative-D study (n = 150) was performed. Fatigue assessed with the Edmonton Symptom Assessment Scale (ESAS) was reduced in vitamin-D-treated men; −1.50 ESAS points (95%CI −2.57 to −0.43; p = 0.007) but not in women; −0.75 (95%CI −1.85 to 0.36; p = 0.18). Fatigue measured with EORTC QLQ-C15-PAL had a borderline significant effect in men (−0.33 (95%CI −0.67 to 0.03; p = 0.05)) but not in women (p = 0.55). The effect on fatigue measured with ESAS in men remained the same after adjustment for opioid doses (p = 0.01). In conclusion, the positive effect of the correction of vitamin D deficiency on fatigue may be more pronounced in men than in women. However, studies focused on analyzing sex differences in this context must be performed before firm conclusions can be drawn.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".