25-hydroxyvitamin D serum levels in patients with high risk resected melanoma treated in an adjuvant bevacizumab trial
Bibliographic record
Abstract
BACKGROUND: Studies evaluating a relationship of vitamin D in patients with primary melanoma have consistently identified an inverse correlation with Breslow thickness, but an inconsistent impact on survival. Vitamin D in later stages of melanoma has been less studied. METHODS: Vitamin D was measured in serum from 341 patients with resected stage IIB-IIIC melanoma recruited to the AVAST-M adjuvant melanoma randomised trial, collected prior to randomisation, then at 3 and 12 months. Vitamin D levels were compared with patient demographics, known melanoma prognostic factors, disease-free interval (DFI) and overall survival (OS). RESULTS: A total of 73% patients had stage III melanoma, 32% were enroled (and therefore tested) >1 year after primary melanoma diagnosis. Median pre-randomisation vitamin D level was 56.5 (range 12.6-189.0 nmol/L). Vitamin D levels did not significantly vary over 12 months (p = 0.24). Individual pre-randomisation vitamin D levels did not differ significantly for Breslow thickness, tumour ulceration, or disease stage. Neither did pre-randomisation vitamin D predict for DFI (HR = 0.98 per 10 nmol/L increase; 95% confidence interval (CI) 0.93-1.04, p = 0.59) or OS (HR = 0.96 per 10 nmol/L increase, 95% CI 0.90-1.03, p = 0.31). For stage II patients, DFI improved with higher pre-randomisation vitamin D levels for those on bevacizumab (HR = 0.74 per 10 nmol nmol/L increase; 95% CI 0.56-0.97), but not for the observation arm (HR = 1.07 per 10 nmol/L increase; 95% CI 0.85-1.34). CONCLUSIONS: In this stage II/III melanoma cohort, vitamin D did not correlate with known prognostic markers, nor predict for DFI or OS, but there was some evidence of benefit for patients with stage II disease treated with bevacizumab.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".