Hereditary colorectal cancer screening: A 10-year longitudinal cohort study following an educational intervention
Bibliographic record
Abstract
Family history (FH) of a first-degree relative with colorectal cancer (CRC) is associated with two to fourfold increased risk, yet screening uptake is suboptimal despite proven mortality reduction. We developed a FH-based CRC Risk Triage/Management tool for family physicians (FPs), and educational booklet for patients with CRC FH. This report describes physician referral and patient screening behavior 5 and 10 years post-educational intervention, and factors associated with screening. Longitudinal cohort study. FPs/patients in Ontario and Newfoundland, Canada were sent questionnaires at baseline (2005), 5 and 10 years (2015) following tool/booklet receipt. FPs were asked about CRC screening, patients about FH, screening type and timing. "Correct" screening was concordance with tool recommendations. Results reported for 29/121 (24%) FPs and 98/297 (33%) patients who completed all 3 questionnaires. Over 10 years 2/3 patients received the correct CRC screening test at appropriate timing (baseline 75%, 5-year 62%, 10-year 65%). About half reported their FP recommended CRC screening (5-year 51%, 10-year 63%). Fewer than half the patients correctly assessed their CRC risk (44%, 40%, 41%). Patients were less likely to have correct screening timing if female (RR 0.78; 95% CI 0.61, 0.99; p = 0.045). Patients were less likely to have both correct test and timing if moderate/high CRC risk (RR 0.66; 95% CI 0.47, 0.93; p = 0.017) and more likely if their physician recommended screening (RR1.69; 95% CI 1.15, 2.49; p = 0.007). Physician discussion of CRC risk and screening can positively impact patient screening behavior. Efforts are particularly needed for women and patients at moderate/high CRC risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 teacher head, 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".