Assessment of moderate coffee consumption and risk of epithelial ovarian cancer: a Mendelian randomization study
Bibliographic record
Abstract
Background: Coffee consumption has been shown to be associated with various health outcomes in observational studies. However, evidence for its association with epithelial ovarian cancer (EOC) is inconsistent and it is unclear whether these associations are causal. Methods: We used single nucleotide polymorphisms associated with (i) coffee and (ii) caffeine consumption to perform Mendelian randomization (MR) on EOC risk. We conducted a two-sample MR using genetic data on 44 062 individuals of European ancestry from the Ovarian Cancer Association Consortium (OCAC), and combined instrumental variable estimates using a Wald-type ratio estimator. Results: For all EOC cases, the causal odds ratio (COR) for genetically predicted consumption of one additional cup of coffee per day was 0.92 [95% confidence interval (CI): 0.79, 1.06]. The COR was 0.90 (95% CI: 0.73, 1.10) for high-grade serous EOC. The COR for genetically predicted consumption of an additional 80 mg caffeine was 1.01 (95% CI: 0.92, 1.11) for all EOC cases and 0.90 (95% CI: 0.73, 1.10) for high-grade serous cases. Conclusions: We found no evidence indicative of a strong association between EOC risk and genetically predicted coffee or caffeine levels. However, our estimates were not statistically inconsistent with earlier observational studies and we were unable to rule out small protective associations.
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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 | 0.004 | 0.008 |
| 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".