Abstract 4652: Intake of dietary fruit, vegetables, and fiber and risk of colorectal cancer according to molecular subtypes: A pooled analysis
Bibliographic record
Abstract
Abstract Background and Objectives: While there is a clear association between many lifestyle-related factors and colorectal cancer (CRC) risk, the protective associations of fruit, vegetables, and fiber intake have been shown in many, but not all epidemiological studies. One possible reason for study heterogeneity is that dietary factors may have distinct effects by CRC molecular subtypes. To explore this hypothesis, we investigated the association between fruit, vegetables, and fiber intake and four well-established CRC molecular characteristics. Methods: We analyzed 9 observational studies including 8,783 CRC cases with molecular tumor markers for microsatellite instability (MSI), the CpG island methylator phenotype (CIMP), and somatic mutations in BRAF (V600E) and KRAS (codon 12 or 13), and 7,869 controls. We used case-only and polytomous logistic regression analyses to assess the association between dietary intake of fruit, vegetables, and fiber with CRC molecular subtypes defined by each marker separately and in combination. Results: We found that higher fruit intake was associated with a decreased risk of BRAF-mutated tumors [Odds ratio (OR) 4th vs. 1st quartile = 0.72 (95% confidence interval (CI) = 0.57-0.91)], but not with BRAF-wildtype tumor [OR 4th vs. 1st quartile = 1.01 (95%CI = 0.90-1.13); p-difference = 3e-03]. Higher fiber intake showed significant negative association with MSS/MSI-low, CIMP-negative, BRAF-wildtype, and KRAS-wildtype when using these markers separately and in combination (p-trend range from 2e-03 to 4e-05). These negative associations were stronger compared with MSI-high, CIMP-positive, BRAF-mutated or KRAS-mutated tumors, but the differences were not statistically significant. Conclusion: Higher fruit intake may be associated with a decreased risk of BRAF-mutated CRC but not with BRAF-wildtype CRC. Additionally, higher fiber intake may be associated with a decreased risk of MSS/MSI-low, CIMP-negative, BRAF-wildtype, and KRAS-wildtype tumors. These results may explain in part the inconsistent findings between fruit or fiber intake and overall CRC risk that have previously been reported. Citation Format: Akihisa Hidaka, Harrison A. Tabitha, Daniel D. Buchanan, Michael Hoffmeister, Marc J. Gunter, Xiaoliang Wang, Yi Lin, Wei Sun, Syed H. Zaidi, Martha L. Slattery, Bethany Van Guelpen, Steven J. Gallinger, Michael O. Woods, Mark A. Jenkins, Shuji Ogino, Polly A. Newcomb, Peter T. Campbell, Li Hsu, Ulrike Peters. Intake of dietary fruit, vegetables, and fiber and risk of colorectal cancer according to molecular subtypes: A pooled analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4652.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.021 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".