Are United States and Canadian Cancer Screening Rates Consistent With Guideline Information Regarding the Age of Screening Initiation
Bibliographic record
Abstract
Objective. To understand whether US and Canadian breast, colorectal and prostate cancer screening test utilization is consistent with US and Canadian cancer screening guideline information with respect to the age of screening initiation. Design. Cross-sectional, regression discontinuity. Setting. Canada and US. Participants. Canadian and US women of ages 30–60 and men of ages 40–6'3 Interventions. None. Main Outcomes Measures. Mammography, prostate-specific antigen (PSA) and colorectal cancer test use within the past 2 years. Methods. We identify US and Canadian compliance with age screening information in a novel manner, by comparing test utilization rates of individuals who are immediately on either side of the guideline recommended initiation ages. Results. US mammography utilization within the last 2 years increased from 33% at age 39 to 48% at age 40 and 60% at age 41. US colorectal cancer test utilization, within the last 2 years, increased from 15% at age 49 to 18% at age 50 and 28% at age 51. US PSA utilization within the last 2 years increased from 37% at age 49 to 44% at age 50 and 54% at age 51. In Canada, mammography utilization within the last 2 years increased from 47% at age 49 to 57% at age 50 and 66% at age 51. Conclusion. US and Canadian cancer screening utilization is generally consistent with each country’s guideline recommendations regarding age. US and Canadian differences in screening due to guidelines can potentially explain cross-country differences in breast cancer mortality and affect interpretation of international comparisons of cancer statistics.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".