Fecal occult blood versus DNA testing: indirect comparison in a colorectal cancer screening population
Bibliographic record
Abstract
Background: A multitarget stool DNA test (MSDT) that showed higher sensitivity but lower specificity than a fecal immunochemical test (FIT) for hemoglobin in one recent study from the US and Canada, is increasingly used for colorectal cancer (CRC) screening, despite its ~20-fold higher costs compared to FITs. We aimed to assess diagnostic performance of a quantitative FIT in an independent study among participants of screening colonoscopy and to compare it with the previously reported performance of MSDT. Methods: A total of 3494 participants, aged 50–84 years, who underwent screening colonoscopy in private gastroenterological practices in Germany, and who provided a stool sample before colonoscopy to be evaluated by a commercially available quantitative FIT ( FOB Gold ® ) were included. Diagnostic performance (sensitivity, specificity) for detecting CRC or advanced precancerous lesions (APCLs) was evaluated by comparison of test results with findings at screening colonoscopy. In addition to the original cutoff, we used an adjusted cutoff yielding the same specificity as reported for the MSDT to enhance comparability. Results: The most advanced finding at colonoscopy was CRC and APCL in 30 (0.86%) and 359 (10.3%) cases, respectively. At a cutoff yielding the same specificity as reported for MSDT (86.6%), the sensitivities (95% CI) of the FIT for detecting CRC and APCL >1 cm were 96.7% (82.8–99.9%) and 54.3% (48.3–60.3%), respectively. These sensitivities are higher than those reported for MSDT (92.3% and 43.6%, p =0.66 and 0.003, respectively). Conclusion: In this large screening population, FIT showed equivalent or better diagnostic performance in comparison to reported performance of MSDT. Keywords: colorectal cancer screening, fecal occult blood test, fecal immunochemical test, sensitivity, specificity, test performance A Letter to the Editor has been received and published for this article.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".