Decreased Colorectal Cancer Incidence and Incidence-Based Mortality in the Screening-Age Population of Ontario
Bibliographic record
Abstract
BACKGROUND AND AIMS: We aimed to evaluate trends in Ontario, Canada, 2002 to 2016, in uptake of colorectal evaluative procedures, colorectal cancer (CRC) incidence and incidence-based mortality in the colorectal screening-age population. METHODS: We defined the screening age-eligible population as persons 51 to 74 years of age with ≥1 year eligibility for the Ontario Health Insurance Plan, excluding those with a diagnosis of CRC in the Ontario Cancer Registry (OCR) prior to age 50 or January 1, 2002. We computed annual up-to-date status with colorectal evaluative procedures from billing claims, and CRC incidence from the OCR. In order to compute incidence-based CRC mortality, we included persons with a first diagnosis of CRC between the ages of 51 and 74, diagnosed between January 1, 1992 and December 31, 2001, still alive and <75 years of age on January 1, 2002, based on cause of death from the OCR. Overall, age-stratified and sex-stratified trends were evaluated by Cochran-Armitage trend tests. RESULTS: Persons up to date with colorectal evaluative procedures increased from 628,214/2,782,061 (22.6%) in 2002 to 2,584,570/4,179,789 (62.2%) in 2016. CRC incidence fell from 129.3/100,000 in 2002 to 94.54/100,000 in 2016, and incidence-based CRC mortality fell from 40.8/100,000 to 24.1/100,000. Decreasing trends in overall and stratified incidence and mortality were all significant, except among persons 51 to 54 years old. CONCLUSIONS: There was continued increase in persons up-to-date with colorectal evaluative procedures, and significant decrease in CRC incidence and incidence-based CRC mortality from 2002 through 2016.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".