Circulating 25-Hydroxyvitamin D, <i>VDR</i> Polymorphisms, and Survival in Advanced Non–Small-Cell Lung Cancer
Bibliographic record
Abstract
PURPOSE: We showed previously that in early-stage non-small-cell lung cancer (NSCLC), serum vitamin D levels and VDR polymorphisms were associated with survival. We hypothesized that vitamin D levels and VDR polymorphisms may also affect survival among patients with advanced NSCLC. PATIENTS AND METHODS: We evaluated the relationship between circulating 25-hydroxyvitamin D levels; VDR polymorphisms, including Cdx-2 G>A (rs11568820), FokI C>T (rs10735810), and BsmI C>T (rs144410); and overall survival among patients with advanced NSCLC. Analyses of survival outcomes were performed using the log-rank test and Cox proportional hazards models, adjusting for sex, stage, and performance status. RESULTS: There were 294 patients and 233 deaths, with median follow-up of 42 months. We found no difference in survival by circulating vitamin D level. The C/C genotype of the FokI polymorphism was associated with improved survival: median survival for C/C was 21.4 months, for C/T was 12.1 months, and for T/T was 15.6 months (log-rank P = .005). There were no significant effects on survival by the Cdx-2 or BsMI polymorphism. However, having increasing numbers of protective alleles was associated with improved survival (adjusted hazard ratio for two or more v zero to one protective alleles, 0.57; 95% CI, 0.41 to 0.79; P = .0008). On haplotype analysis, the G-T-C (Cdx-2-FokI-BsmI) haplotype was associated with worse survival compared with the most common haplotype of G-C-T (adjusted hazard ratio, 1.61; 95% CI, 1.21 to 2.14; P = .001). CONCLUSION: There was no main effect of vitamin D level on overall survival in the advanced NSCLC population. The T allele of the VDR FokI>T polymorphism and the G-T-C (Cdx-2-FokI-BsmI) haplotype were associated with worse survival.
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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 | 0.000 |
| 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".