Genetic sequence variants in vitamin D metabolism pathway genes, serum vitamin D level and outcome in head and neck cancer patients
Bibliographic record
Abstract
Although some studies have reported associations between serum vitamin D level and prognosis in several cancers, others have found associations between genetic sequence variants (GSVs) in the vitamin D metabolism pathway genes and outcomes in various cancers including head and neck cancer (HNC). We comprehensively evaluated the association and interaction of GSVs in vitamin D metabolism pathway genes and their regulatory effects on circulatory serum vitamin D level in HNC outcome. We systemically evaluated the association of 89 tagging and candidate-based GSVs in six major vitamin D metabolism pathway genes (VDR, GC, CYP24A1, CYP27A1, CYP27B1 and CYP2R1) and the circulating serum vitamin D level with overall survival (OS) and second primary cancer (SPC) in 522 Stages I-II radiation-treated patients with HNC. For OS: median follow-up time was 8 years; for SPC, 4.4 years. The most common subsite was the larynx (84%). Three hundred and twelve patients were alive at the end of follow-up for OS. SPCs were diagnosed in 108 patients and were primarily of lung (46%). Serum vitamin D levels were significantly lower in patients carrying the minor alleles of GC:rs4588 and CYP2R1:rs10500804. CYP24A1:rs2296241 was significantly associated with OS and CYP2R1:rs1993116 was with SPC. These two GSVs remained significantly associated after adjusting for serum vitamin D level and important clinical factors. GSVs in the vitamin D metabolism pathway genes were associated with disease outcomes in HNC patients; however, these GSVs are different from those affecting serum vitamin D levels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".