Correlating Quantitative Fecal Immunochemical Test Results with Neoplastic Findings on Colonoscopy in a Population-Based Colorectal Cancer Screening Program: A Prospective Study
Bibliographic record
Abstract
Background and Aims. The Canadian Partnership Against Cancer (CPAC) recommends a fecal immunochemical test- (FIT-) positive predictive value (PPV) for all adenomas of ≥50%. We sought to assess FIT performance among average-risk participants of the British Columbia Colon Screening Program (BCCSP).Methods.From Nov-2013 to Dec-2014 consecutive participants of the BCCSP were assessed. Data was obtained from a prospectively collected database. A single quantitative FIT (NS-Plus, Alfresa Pharma Corporation, Japan) with a cut-off of ≥10 μg/g (≥50 ng/mL) was used.Results. 20,322 FIT-positive participants underwent CSPY. At a FIT cut-off of ≥10 μg/g (≥50 ng/mL) the PPV for all adenomas was 52.0%. Increasing the FIT cut-off to ≥20 μg/g (≥100 ng/mL) would increase the PPV for colorectal cancer (CRC) by 1.5% and for high-risk adenomas (HRAs) by 6.5% at a cost of missing 13.6% of CRCs and 32.4% of HRAs.Conclusions.As the NS-Plus FIT cut-off rises, the PPV for CRC and HRAs increases but at the cost of missed lesions. A cut-off of ≥10 μg/g (≥50 ng/mL) produces a PPV for all adenomas exceeding national recommendations. Health authorities need to take into consideration endoscopic resources when selecting a FIT positivity threshold.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".