Alcohol consumption and colon cancer prognosis among participants in north central cancer treatment group phase III trial N0147
Bibliographic record
Abstract
Alcohol consumption is associated with a modest increased risk of colon cancer, but its relationship with colon cancer survival has not been elucidated. Using data from a phase III randomized adjuvant trial, we assessed the association of alcohol consumption with colon cancer outcomes. Patients completed a risk factor questionnaire before randomization to FOLFOX or FOLFOX + cetuximab (N = 1984). Information was collected on lifestyle factors, including smoking, physical activity and consumption of different types of alcohol. Cox models assessed the association between alcohol consumption and outcomes of disease-free survival (DFS), time-to-recurrence (TTR) and overall survival (OS), adjusting for age, sex, study arm, body mass, smoking, physical activity and performance status. No statistically significant difference in outcomes between ever and never drinkers were noted [hazard ratio (HR)DFS = 0.86, HRTTR = 0.87, HROS = 0.86, p-values = 0.11-0.17]. However, when considering alcohol type, ever consumers of red wine (n = 628) had significantly better outcomes than never consumers (HRDFS = 0.80, HRTTR = 0.81, HROS = 0.78, p-values = 0.01-0.02). Favorable outcomes were confirmed in patients who consumed 1-30 glasses/month of red wine (n = 601, HR = 0.80-0.83, p-values = 0.03-0.049); there was a suggestion of more favorable outcomes in patients who consumed >30 glasses/month of red wine (n = 27, HR = 0.33-0.38, p-values = 0.05-0.06). Beer and liquor consumption were not associated with outcomes. Although alcohol consumption was not associated with colon cancer outcomes overall, mild to moderate red wine consumption was suggestively associated with longer OS, DFS and TTR in stage III colon cancer patients.
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".