Canadian colorectal cancer screening programs: How do they measure up using the International Agency for Research on Cancer criteria for organized screening?
Bibliographic record
Abstract
Background: Canada has one of the highest incidences of colorectal cancer (CRC) worldwide. CRC screening improves CRC outcomes and is cost-effective. This study compares Canadian CRC screening programs using essential elements of an organized screening program outlined by the International Agency for Research on Cancer (IARC). Methods: We collaborated with the Cancer Screening in 5 continents (CanScreen5) program, an initiative of IARC. Standardized data collection forms were sent to representatives of provincial and territorial CRC screening programs. Twenty-five questions were selected to reflect IARC's essential elements of an organized screening program. We performed a qualitative analysis of Canada's CRC screening programs and compared programs within Canada and internationally. Results: CRC screening programs exist in 10 provinces and 2 territories. None of the programs in Canada met all the essential criteria of an organized screening program outlined by IARC. Three programs do not send invitations to participate in screening. Among those that do, 4 programs do not include a stool test kit in the invitations. While all provinces met the essential elements for leadership, governance, finance, and access to essential services, there was more heterogeneity in the domains of service delivery as well as information systems and quality assurance. Conclusions: There is considerable heterogeneity in the design of CRC screening programs in Canada and worldwide. Programs should strive to meet all the essential IARC criteria for organized screening if local resources allow, such as issuing invitations and implementing systems to track and compare outcomes to maximize screening program quality, effectiveness, and impact.
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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 | 0.023 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.022 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".