Association Between Colonoscopy Rates and Colorectal Cancer Mortality
Bibliographic record
Abstract
OBJECTIVES: Although colonoscopy use has increased in the United States and Canada since the early 1990s, it is unclear whether this has been associated with benefit at the population level. Our objective was to evaluate the association between regional colonoscopy rates and death from colorectal cancer (CRC). METHODS: We conducted a natural experiment involving a 14-year follow-up of a cohort of all men and women 50-90 years of age living in Ontario on 1 January 1993 exposed to different intensities of colonoscopy use. Each member of the study cohort was assigned to a region each year, on the basis of his/her residence. Each individual was followed up through 31 December 2006; age- and sex-standardized CRC incidence rates were calculated and all CRC deaths were identified. Each year, for each region, the rate of colonoscopies performed on persons 50-90 years of age, per 1,000 population 50-90 years of age, living in the region, was calculated. Multivariable cox proportional hazards models were used to evaluate the association between colonoscopy rate and death from CRC, adjusting for age, sex, comorbidity, income, and location of residence (urban/rural). RESULTS: The study cohort comprised 2,412,077 persons 50-90 years of age. The mean age was 64 years, and 53.7% were women. Colonoscopy rates increased in all regions during 1993-2006. The increased rate of complete colonoscopy was inversely associated with death from CRC. For every 1% increase in complete colonoscopy rate, the hazard of death decreased by 3%. CONCLUSIONS: Increased colonoscopy use was associated with mortality reduction from CRC at the population level.
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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 | 0.000 |
| 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 | 0.000 |
| 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".