Hypothesis and data-driven dietary patterns and colorectal Cancer survival: findings from Newfoundland and Labrador colorectal Cancer cohort
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Dietary patterns are commonly used in epidemiological research, yet there have been few studies assessing if and how research results may vary across dietary patterns. This study aimed to estimate the risk of mortality/recurrence/metastasis using different dietary patterns and comparison amongst the patterns. METHODS: Dietary patterns were identified by Cluster Analysis (CA), Principal Component Analysis (PCA), Alternate Mediterranean Diet score (altMED), Recommended Food Score (RFS) and Dietary Inflammatory Index (DII) scores using a 169-item food frequency questionnaire. Five hundred thirty-two colorectal cancer patients diagnosed between 1999 and 2003 in Newfoundland were followed-up until 2010. Overall Mortality (OM) and combined Mortality, Recurrence or Metastasis (cMRM) were identified. Comparisons were made with adjusted Cox proportional Hazards Ratios (HRs), correlation coefficients and the distributions of individuals in defined clusters by quartiles of factor and index scores. RESULTS: One hundred and seventy cases died from all causes and 29 had a cancer recurrence/metastasis during follow-up. Processed meats as classified by PCA (HR 1.82; 95% confidence interval (CI) 1.07-3.09), clusters characterized by meat and dairy products (HR 2.19; 95% CI 1.03-4.67) and total grains, sugar, soft drinks (HR 1.95; 95% CI 1.13-3.37) were associated with a higher risk of cMRM. Poor adherence to AltMED increased the risk of all-cause OM (HR 1.62; 95% CI 1.04-2.56). Prudent vegetable, high sugar pattern, RFS and DII had no significant association with both OM and cMRM. CONCLUSION: Estimation of OM and cMRM varied across dietary patterns which is attributed to the differences in the foundation of each pattern.
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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