Markers of Vitamin D Exposure and Esophageal Cancer Risk: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Vitamin D has been associated with reduced risk of many cancers, but evidence for esophageal cancer is mixed. To clarify the role of vitamin D, we performed a systematic review and meta-analysis to evaluate the association of vitamin D exposures and esophageal neoplasia, including adenocarcinoma, squamous cell carcinoma (SCC), Barrett's esophagus, and squamous dysplasia. Ovid MEDLINE, EMBASE, and Web of Science were searched from inception to September 2015. Fifteen publications in relation to circulating 25-hydroxyvitamin D [25(OH)D; n = 3], vitamin D intake (n = 4), UVB exposure (n = 1), and genetic factors (n = 7) were retrieved. Higher [25(OH)D] was associated with increased risk of cancer [adenocarcinoma or SCC, OR = 1.39; 95% confidence interval (CI), 1.04-1.74], with the majority of participants coming from China. No association was observed between vitamin D intake and risk of cancer overall (OR, 1.03; 0.65-1.42); however, a nonsignificantly increased risk for adenocarcinoma (OR, 1.45; 0.65-2.24) and nonsignificantly decreased risk for SCC (OR, 0.80; 0.48-1.12) were observed. One study reported a decreased risk of adenocarcinoma with higher UVB exposure. A decreased risk was found for VDR haplotype rs2238135(G)/rs1989969(T) carriers (OR, 0.45; 0.00-0.91), and a suggestive association was observed for rs2107301. In conclusion, no consistent associations were observed between vitamin D exposures and occurrence of esophageal lesions. Further adequately powered, well-designed studies are needed before conclusions can be made. Cancer Epidemiol Biomarkers Prev; 25(6); 877-86. ©2016 AACR.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".