Vitamin D and Fatigue in Palliative Cancer: A Cross-Sectional Study of Sex Difference in Baseline Data from the Palliative D Cohort
Bibliographic record
Abstract
Background: Fatigue is one of the most distressing symptoms in patients with advanced cancer. Previous studies have shown an association between low vitamin D levels and fatigue. Objectives: The aim of this study was to investigate the association between vitamin D levels and self-assessed fatigue in cancer patients admitted to palliative care, with focus on possible sex differences. Design: This is a cross-sectional study. Subjects: Baseline data from 530 screened patients, 265 women and 265 men, from the randomized placebo-controlled trial “Palliative-D” were analyzed. Measurements: Vitamin D status was measured as 25-hydroxyvitamin D (25-OHD) and fatigue was assessed with EORTC-QLQ-PAL15 and with Edmonton Symptom Assessment System (ESAS). Results: In men, there was a significant correlation between 25-OHD and fatigue measured with the “Tiredness question” (Q11) in EORTC-QLQ-PAL15 (p < 0.05), where higher 25-OHD levels were associated with less fatigue. No correlation between 25-OHD and fatigue was seen for women. Fatigue measured with ESAS did not show any significant association with 25-OHD levels neither in men nor in women. Conclusion: Low vitamin D levels were associated with more fatigue in men but not in women. The study underscores the importance of subgroup analysis of men and women when evaluating the effect of vitamin D in clinical trials since the effect may differ between the sexes. The ongoing “Palliative-D study” will reveal whether vitamin D supplementation may counteract fatigue in both men and women. ClinicalTrial.gov: NCT03038516.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".