Association Between Colonoscopy and Colorectal Cancer Mortality in a US Cohort According to Site of Cancer and Colonoscopist Specialty
Bibliographic record
Abstract
PURPOSE: We designed this study to evaluate the association of colonoscopy with colorectal cancer (CRC) death in the United States by site of CRC and endoscopist specialty. METHODS: We designed a case-control study using Surveillance, Epidemiology, and End Results (SEER)-Medicare data. We identified patients (cases) diagnosed with CRC age 70 to 89 years from January 1998 through December 2002 who died as a result of CRC by 2007. We selected three matched controls without cancer for each case. Controls were assigned a referent date (date of diagnosis of the case). Colonoscopy performed from January 1991 through 6 months before the diagnosis/referent date was our primary exposure. We compared exposure to colonoscopy in cases and controls by using conditional logistic regression controlling for covariates, stratified by site of CRC. We determined endoscopist specialty by linkage to the American Medical Association (AMA) Masterfile. We assessed whether the association between colonoscopy and CRC death varied with endoscopist specialty. RESULTS: We identified 9,458 cases (3,963 proximal [41.9%], 4,685 distal [49.5%], and 810 unknown site [8.6%]) and 27,641 controls. In all, 11.3% of cases and 23.7% of controls underwent colonoscopy more than 6 months before diagnosis. Compared with controls, cases were less likely to have undergone colonoscopy (odds ratio [OR], 0.40; 95% CI, 0.37 to 0.43); the association was stronger for distal (OR, 0.24; 95% CI, 0.21 to 0.27) than proximal (OR, 0.58; 95% CI, 0.53 to 0.64) CRC. The strength of the association varied with endoscopist specialty. CONCLUSION: Colonoscopy is associated with a reduced risk of death from CRC, with the association considerably and consistently stronger for distal versus proximal CRC. The overall association was strongest if colonoscopy was performed by a gastroenterologist.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".