Diet and prostate cancer risk with specific focus on dairy products and dietary calcium: A case–control study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Despite the prevalence of prostate cancer worldwide, only a few risk factors have been well-established. The role of diet, especially of dairy products, in the etiology of prostate cancer is still controversial. METHODS: This study assessed the association of dietary components, particularly dairy products and dietary calcium, on prostate cancer risk in a case-control study of 197 cases and an equal number of individually matched controls recruited in Montreal, Canada. A semi-quantitative food frequency questionnaire was administered in which the usual consumption frequency and amounts consumed of more than 200 food items were recorded. RESULTS: We found a twofold increased risk of prostate cancer associated with an increased intake of dairy products {Odds Ratio (OR) = 2.19; 95% Confidence Intervals (CI) 1.22-3.94}. A significant trend of decreasing prostate cancer risk with higher intake was found for legumes, nuts, finfish/shellfish and for alpha-tocopherol after adjustment for calcium intake. Milk was the only dairy product significantly associated with prostate cancer risk, with OR = 2.27; 95% CI (1.25-4.09) for the highest versus lowest quartiles of consumption. Calcium, the main micronutrient contained in dairy products, showed only a borderline association with prostate cancer risk (P = 0.09), with slightly higher risk for higher calcium intake. In conclusion, this study supports the hypothesis that dairy products, especially milk, are involved in the etiology of prostate cancer. However, the mechanisms by which the various nutrients in dairy products and total diet may interact to influence this risk remain unknown.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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 it