Performance of a quantitative fecal immunochemical test in a colorectal cancer screening pilot program: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: British Columbia undertook a colorectal cancer screening pilot program in 3 communities. Our objective was to assess the performance of 2-specimen fecal immunochemical testing in the detection of colorectal neoplasms in this population-based screening program. METHODS: A prospective cohort of asymptomatic, average-risk people aged 50 to 74 years completed 2 quantitative fecal immunochemical tests every 2 years, with follow-up colonoscopy if the result of either test was positive. Participant demographics, fecal immunochemical test results, colonoscopy quality indicators and pathology results were recorded. Non-screen-detected colorectal cancer that developed in program participants was identified through review of data from the BC Cancer Registry. RESULTS: A total of 16 234 people completed a first round of fecal immunochemical testing, with a positivity rate of 8.6%; 5378 (86.0% of eligible participants) completed a second round before the end of the pilot program, with a positivity rate of 6.7%. Of the 1756 who had a positive test result, 1555 (88.6%) underwent colonoscopy. The detection rate of colorectal cancer was 3.5 per 1000 participants. The positive predictive value of the fecal immunochemical test was 4.9% (95% confidence interval [CI] 3.8%-6.0%) for colorectal cancer, 35.0% (95% CI 32.5%-37.2%) for high-risk polyps and 62.0% (95% CI 59.6%-64.4%) for all neoplasms. The number needed to screen was 283 to detect 1 cancer, 40 to detect 1 high-risk polyp and 22 to detect any neoplasm. INTERPRETATION: Screening every 2 years with a 2-specimen fecal immunochemical test surpassed the current benchmark for colorectal cancer detection in population-based screening. This study has implications for other jurisdictions planning colorectal cancer screening programs.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".