Circulating 25-Hydroxyvitamin D and Risk of Epithelial Ovarian Cancer: Cohort Consortium Vitamin D Pooling Project of Rarer Cancers
Bibliographic record
Abstract
A role for vitamin D in ovarian cancer etiology is supported by ecologic studies of sunlight exposure, experimental mechanism studies, and some studies of dietary vitamin D intake and genetic polymorphisms in the vitamin D receptor. However, few studies have examined the association of circulating 25-hydroxyvitamin D (25(OH)D), an integrated measure of vitamin D status, with ovarian cancer risk. A nested case-control study was conducted among 7 prospective studies to evaluate the circulating 25(OH)D concentration in relation to epithelial ovarian cancer risk. Logistic regression models were used to estimate odds ratios and 95% confidence intervals among 516 cases and 770 matched controls. Compared with 25(OH)D concentrations of 50-<75 nmol/L, no statistically significant associations were observed for <37.5 (odds ratio (OR) = 1.21, 95% confidence interval (CI): 0.87, 1.70), 37.5-<50 (OR = 1.03, 95% CI: 0.75, 1.41), or > or =75 (OR = 1.11, 95% CI: 0.79, 1.55) nmol/L. Analyses stratified by tumor subtype, age, body mass index, and other variables were generally null but suggested an inverse association between 25(OH)D and ovarian cancer risk among women with a body mass index of > or =25 kg/m(2) (P(interaction) < 0.01). In conclusion, this large pooled analysis did not support an overall association between circulating 25(OH)D and ovarian cancer risk, except possibly among overweight women.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.003 |
| 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".