Intake of the major carotenoids and the risk of epithelial ovarian cancer in a pooled analysis of 10 cohort studies
Bibliographic record
Abstract
Carotenoids, found in fruits and vegetables, have the potential to protect against cancer because of their properties, including their functions as precursors to vitamin A and as antioxidants. We examined the associations between intakes of alpha-carotene, beta-carotene, beta-cryptoxanthin, lutein/zeaxanthin and lycopene and the risk of invasive epithelial ovarian cancer. The primary data from 10 prospective cohort studies in North America and Europe were analyzed and then pooled. Carotenoid intakes were estimated from a validated food frequency questionnaire administered at baseline in each study. Study-specific relative risks (RR) were estimated using the Cox proportional hazards model and then combined using a random-effects model. Among 521,911 women, 2,012 cases of ovarian cancer occurred during a follow-up of 7-22 years across studies. The major carotenoids were not significantly associated with the risk of ovarian cancer. The pooled multivariate RRs (95% confidence intervals) were 1.00 (0.95-1.05) for a 600 microg/day increase in alpha-carotene intake, 0.96 (0.93-1.03) for a 2,500 microg/day increase in beta-carotene intake, 0.99 (0.97-1.02) for a 100 microg/day increase in beta-cryptoxanthin intake, 0.98 (0.94-1.03) for a 2,500 microg/day increase in lutein/zeaxanthin intake and 1.01 (0.97-1.05) for a 4,000 microg/day increase in lycopene intake. These associations did not appreciably differ by study (p-values, tests for between-studies heterogeneity >0.17). Also, the observed associations did not vary substantially by subgroups of the population or by histological type of ovarian cancer. These results suggest that consumption of the major carotenoids during adulthood does not play a major role in the incidence of ovarian cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".