Smoking and Colorectal Cancer in Lynch Syndrome: Results from the Colon Cancer Family Registry and The University of Texas M.D. Anderson Cancer Center
Bibliographic record
Abstract
PURPOSE: Lynch syndrome family members with inherited germline mutations in DNA mismatch repair (MMR) genes have a high risk of colorectal cancer (CRC), and cases typically have tumors that exhibit a high level of microsatellite instability (MSI). There is some evidence that smoking is a risk factor for CRCs with high MSI; however, the association of smoking with CRC among those with Lynch syndrome is unknown. EXPERIMENTAL DESIGN: A multicentered retrospective cohort of 752 carriers of pathogenic MMR gene mutations was analyzed, using a weighted Cox regression analysis, adjusting for sex, ascertainment source, the specific mutated gene, year of birth, and familial clustering. RESULTS: Compared with never smokers, current smokers had a significantly increased CRC risk [adjusted hazard ratio (HR), 1.62; 95% confidence interval (95% CI), 1.01-2.57] and former smokers who had quit smoking for 2 or more years were at decreased risk (HR, 0.53; 95% CI, 0.35-0.82). CRC risk did not vary according to age at starting. However, light smoking (<10 cigarettes per day) and shorter duration of smoking (<10 years) were associated with decreased CRC risk (HR, 0.51; 95% CI, 0.29-0.91 and HR, 0.52; 95% CI, 0.30-0.89, respectively). For former smokers, CRC risk decreased with years since quitting (P trend <0.01). CONCLUSIONS: People with Lynch syndrome may be at increased risk of CRC if they smoke regularly. Although our data suggest that former smokers, short-term smokers, and light smokers are at decreased CRC risk, these findings need further confirmation, preferably using prospective designs.
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 | 0.001 | 0.002 |
| 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".