Effectiveness of an organized colorectal cancer screening program on increasing adherence in asymptomatic average-risk Canadians
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) is the third most commonly diagnosed cancer and second highest cause of cancer-related mortality in Canada. Despite the availability of screening services and establishment of guidelines, utilization of colorectal cancer screening in Canada remains low. In 2008, the province of Ontario launched ColonCancerCheck, an organized colorectal cancer screening program aimed at increasing CRC screening adherence. In this study, we adopt a quasi-experimental approach to estimate and describe the impact of ColonCancerCheck on screening behavior in the asymptomatic average risk population. METHODS: Annual screening rates from the target population were estimated using five cycles of the Canadian Community Health Survey, a cross-sectional nationally representative survey of health status, healthcare use, and determinants of health in the Canadian population. We used a difference-in-differences design to measure the overall impact of ColonCancerCheck on past-year fecal occult blood testing (FOBT) and endoscopy in Ontario relative to the rest of Canada. Several verification tests validated the suitability of our model specification. RESULTS: The difference-in-differences analysis shows that ColonCancerCheck increased FOBT screening in the average risk population by 5.2 percentage points (95% CI [3.2, 7.2]), an increase of 33% relative to pre-program screening rates. The program had no observed effect on endoscopy screening and we found no evidence that ColonCancerCheck differentially altered the screening practices of population sub-groups. CONCLUSIONS: Our findings suggest ColonCancerCheck has been successful at increasing use of FOBT in the asymptomatic average risk population.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".