Influence of prediagnostic dietary patterns and cigarette smoking \non colorectal cancer survival: a cohort study
Bibliographic record
Abstract
Cigarette smoking and dietary patterns are associated with colorectal cancer \n(CRC) incidence; however, little is known about their influence on survival after CRC \ndiagnosis. This study was designed to: 1) investigate the association of dietary \npatterns with all-cause (overall survival; OS) and disease-free survival (DFS) among \nCRC patients; 2) examine the association of smoking with OS and DFS among CRC \npatients. \nA cohort of 750 CRC patients diagnosed from 1999 to 2003 in the Canadian \nprovince of Newfoundland and Labrador was followed for mortality and recurrence \nuntil April 2010. Participants reported their smoking history and dietary intakes using \na personal history questionnaire and a food frequency questionnaire. Dietary patterns \nwere identified with factor analysis. Multivariate hazard ratios (HRs) and 95% \nconfidence intervals (CIs) were calculated with Cox proportional hazards regression, \ncontrolling for major known prognostic factors. \nResults from this study are presented in two parts: 1) Disease-free survival among \nCRC patients was significantly worsened among patients with a high dietary intake of \nprocessed meat (the highest versus the lowest quartile HR: 1.82, 95%CI: 1.07-3.09). \nNo associations were observed with the prudent vegetable or the high sugar patterns \nand DFS. The association between the processed meat pattern and survival in CRC \npatients was restricted to patients diagnosed with colon cancer (the highest versus the \nlowest quartile: DFS: HR: 2.29, 95%CI: 1.19-4.40; OS: HR: 2.13, 95%CI: 1.03-4.43). \nPotential effect modification was noted for sex (DFS: P=0.04, HR: 3.85 for women \nand 1.22 for men). 2) Compared with never smoking, current (HR: 1.78; 95%CI: \n1.04-3.06), but not former (HR: 1.06; 95%CI: 0.71-1.59), smoking was associated \nwith decreased OS, although this association was limited to tumors in the colon. The associations of cigarette smoking with the study outcomes were higher among patients \nwith >40 pack-years of smoking (OS: HR: 1.72; 95%CI: 1.03-2.85; DFS: HR: 1.99; \n95%CI: 1.25-3.19). Potential interaction was noted for sex (DFS: P=0.04, HR: 1.68 \nfor men and 1.01 for women) and age at diagnosis (OS: P=0.03, HR: 1.11 for patients \naged < 60 and 1.69 for patients aged 60). \nIn summary, 1) processed meat dietary pattern prior to diagnosis is associated \nwith higher risk of tumor recurrence, metastasis, or death from any cause among \ncolon cancer patients; 2) pre-diagnosis cigarette smoking is associated with worsened \nprognosis among patients with colon cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".