Impact of smoking on patients with stage III colon cancer
Bibliographic record
Abstract
BACKGROUND: Cigarette smoking has been shown to increase the risk of developing colorectal cancer, particularly smoking early in life. Little is known about the impact of tobacco use on colon cancer recurrence among colon cancer survivors. METHODS: The authors prospectively collected lifetime smoking history from stage III colon cancer patients enrolled in a phase 3 trial via self-report questionnaires during and 6 months after completion of adjuvant chemotherapy. Smoking status was defined as never, current, or past. Lifetime pack-years were defined as number of lifetime packs of cigarettes. Patients were followed for recurrence or death. RESULTS: Data on smoking history were captured on 1045 patients with stage III colon cancer receiving adjuvant therapy (46% never smokers; 44% past; 10% current). The adjusted hazard ratio (HR) for disease-free survival (DFS) was 0.99 (95% confidence interval [CI], 0.70-1.41), 1.17 (95% CI 0.89-1.55), and 1.22 (95% CI 0.92-1.61) for lifetime pack-years 0-10, 10-20, and 20+, respectively, compared with never smoking (P = .16). In a preplanned exploratory analysis of smoking intensity early in life, the adjusted HR for 12+ pack-years before age 30 years for DFS was 1.37 (95% CI, 1.02-1.84) compared with never smoking (P = .04). The adjusted HR for DFS was 1.18 (95% CI, 0.92-1.50) for past smokers and 1.10 (95% CI, 0.73-1.64) for current smokers, compared with never smokers. CONCLUSIONS: Total tobacco usage early in life may be an important, independent prognostic factor of cancer recurrences and mortality in patients with stage III 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".