Guidance for faecal occult blood testing: quantitative immunochemical method (FIT-HB) in colorectal cancer screening programmes.
Bibliographic record
Abstract
BACKGROUND: in Italy, colorectal cancer screening is included as part of the Italian National Health Service - SSN (Servizio Sanitario Nazionale) Essential Levels of Care - LEA (Livelli Essenziali Assistenziali) and the European Guidelines, which specify quantitative FIT-Hb testing as the best strategy for organised screening programmes. To ensure consistent operating standards in Member States, European regulations require the implementation of certification and accreditation requirements for diagnostic and care-related processes. The requirement, based on ISO 17021 accreditation standards, includes ISO 9001 certification for systems and ISO 15189:2012 accreditation for laboratories. METHODOLOGY: various phases of the analytical process (pre-test, test, post-test) were evaluated in detail and provided operational guidelines for adjusting analytical and managerial procedures using: (a) feedback from members of GISCoR screening labs; (b) performance data obtained via a systematic review of the literature and the Osservatorio Nazionale Screening (ONS) Survey; (c) recommendations for laboratory practice issued by the World Endoscopy Organization "FIT for Screening" Working Group; (d) selected guidelines from the National Guidelines Clearinghouse database; and (e) Canadian, Australian and European screening programme websites. With respect to ISO 15189:2012 standards for accreditation of medical laboratories, GISCoR's guidance has been re-evaluated and revised by auditors from the Italian certification body (ACCREDIA) to assess its compliance and completeness with the aim of finalising operating procedures. CONCLUSIONS: the implementation and maintenance of operational standards required by complex systems (e.g. screening programmes) involving constant interaction between facilities and the supporting organisational structure are not easy to achieve. The guide aims to provide laboratories with the necessary guidance for proper process management.
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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 | 0.016 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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".