A Comparison of the Diagnostic Performance of Guaiac and Immunochemical Fecal Occult Blood Tests with Colonoscopy for the Detection of Colorectal Neoplasia
Bibliographic record
Abstract
Purpose: While screening for colorectal neoplasia using fecal occult blood tests (FOBTs) has demonstrated a reduction in colorectal cancer morbidity and mortality, consensus has not been reached as to the best FOBT to use in large scale population screening initiatives. Our aim was to compare the diagnostic performance characteristics of the guaiac-based (G-FOBT) Hemoccult II® (Beckman Coulter) and two fecal immunochemical tests (I-FOBT); the Hemoccult ICT® (Beckman Coulter) and MagStream HemSp® (Fujirebio) relative to colonoscopy. Methods: We used a prospective observational cohort design. 1000 asymptomatic individuals were recruited from the wait lists of 20 urban gastroenterology practices in Edmonton, Canada. Both average risk (50-75 years of age) and moderate risk patients (based on family history of colon cancer or previous history of colonic polyps) were recruited from April 2008 to May 2009. At least 1 month prior to the colonoscopy by expert colonoscopists, all subjects attended an educational session and collected three fecal occult blood tests from the same stool at home on 2 consecutive days. No dietary modifications were required. Laboratory technicians and colonoscopists were blinded to results of colonoscopy and FOBT respectively. Results: 1000 patients have been recruited into the study. Results are presented for the first 751 cases. (53.4% female, mean age 56). With colonoscopy, the adenoma detection rate was 24.7%, the advanced adenoma detection rate was 5.7% and the cancer detection rate was 0.3%. The performance characteristics of the 3 occult blood tests were compared relative to the colonoscopic findings as found in Table 1.Table 1: Sensitivity and specificity of G-FOBT and I-FOBTs for colorectal neoplasiaConclusion: Compared to G-FOBT, the I-FOBT tests were more sensitive for colonic advanced adenomas and cancers with a reasonable trade-off in specificity.
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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 | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".