Comprehensive Assessment of Diet Quality and Risk of Precursors of Early-Onset Colorectal Cancer
Bibliographic record
Abstract
BACKGROUND: The role of poor diet quality in the rising incidence of colorectal cancer (CRC) diagnosed younger than age 50 years has not been explored. Based on molecular features of early-onset CRC, early-onset adenomas are emerging surrogate endpoints. METHODS: In a prospective cohort study (Nurses' Health Study II), we evaluated 2 empirical dietary patterns (Western and prudent) and 3 recommendation-based indexes (Dietary Approaches to Stop Hypertension [DASH], Alternative Mediterranean Diet [AMED], and Alternative Healthy Eating Index [AHEI]-2010) with risk of early-onset adenoma overall and by malignant potential (high-risk: ≥1 cm, tubulovillous or villous histology, high-grade dysplasia, or ≥3 adenomas), among 29 474 women with 1 or more lower endoscopy before age 50 years (1991-2011). Multivariable logistic regressions were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: We documented 1157 early-onset adenomas with 375 at high risk. Western diet was positively associated, whereas prudent diet, DASH, AMED, and AHEI-2010 were inversely associated with risk of early-onset adenoma. The associations were largely confined to high-risk adenomas (the highest vs lowest quintile: Western, OR = 1.67, 95% CI = 1.18 to 2.37; prudent, OR = 0.69, 95% CI = 0.48 to 0.98; DASH, OR = 0.65, 95% CI = 0.45 to 0.93; AMED, OR = 0.55, 95% CI = 0.38 to 0.79; AHEI-2010, OR = 0.71, 95% CI = 0.51 to 1.01; all Ptrend ≤ .03), driven by those identified in the distal colon and rectum (all Ptrend ≤ .04, except AMED: Ptrend = .14). CONCLUSION: Poor diet quality was associated with an increased risk of early-onset distal and rectal adenomas of high malignant potential. These findings provide preliminary but strong support to the role of diet in early-onset CRC.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".