A107 ANALYSIS OF THE EFFICACY IN TRANSITIONING FROM FOBT TO FIT FOR COLORECTAL CANCER SCREENING AT A SINGLE CENTRE IN ONTARIO
Notice bibliographique
Résumé
Abstract Background Colonoscopy is the gold standard for detecting colorectal cancer (CRC) and advanced lesions, but is an invasive and carries some risks, with limited availability and accessibility. Alternatively, the fecal occult blood test (FOBT) and fecal immunochemical test (FIT) are both non-invasive, cost-effective screening tests that can also be used to detect CRC, advanced lesions, and polyps, identifying individuals to be prioritized to undergo colonoscopy. FOBT screens for small amounts of blood in stool by detecting heme through a chemical reaction. FIT confirms the presence of blood in stool by using antibodies to detect hemoglobin. Prior to 2019, Ontario employed FOBT as the preferred method for CRC screening in eligible individuals. In early 2019, Ontario transitioned to FIT as the preferred screening test, due its established superior test performance for identifying patients with high risk lesions for colon cancer. Aims This single-centre retrospective study analyzed the change in efficacy of detecting advanced lesions, when transitioning from FOBT to FIT, as identified on subsequent colonoscopy Methods A retrospective chart review was conducted of approximately 1000 patients undergoing colonoscopy for FOBT or FIT at Cambridge Memorial Hospital, covering the period of transition from FOBT to FIT. Colonoscopies were performed by 10 endoscopists. Patients were stratified into 2 groups based on fecal test type, FOBT (N = 344) and FIT (N = 572). Overall and individual proportions of cancer, polyps, adenomas, advanced adenomas (AA), and sessile serrated adenomas (SSA) detection in the subsequent colonoscopies were calculated for both groups. The efficacy of both tests was then assessed using statistical analysis. Results In total, 344 patients were included for FOBT analysis and results included: cancer (5.52%), any polyp (56.69%), adenoma (43.6%), AA (20.64), and SSA (6.1%). In contrast, 572 patients were included for analysis of FIT group and results included: cancer (3.85%), any polyp (83.22%), adenoma (76.92%), AA (43.01), and SSA (12.94%). Cancer detection was similar in the 2 groups. There was significant improvement in polyp, adenoma, advanced adenoma, and sessile serrated adenoma detection with FIT compared to FOBT. This improvement was consistent in all endoscopists, but more pronounced in endoscopists with lower detection rates in FOBT cases. Conclusions The use of FIT as a screening stool test, as compared to FOBT, was associated with a significantly improved detection for polyps, adenomas, AA, and SSA, confirming greater accuracy and sensitivity of FIT as a screening tool. This result confirms the premise, at least at a single institution, that by switching to FIT, Ontario has improved colon cancer screening and prevention with more efficient and higher yield utilization of a limited and costly health care resource Funding Agencies None
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».