MétaCan
Menu
Retour à la cohorte
Enregistrement W4408904107 · doi:10.1136/bmj-2024-082656

Computer aided detection and diagnosis of polyps in adult patients undergoing colonoscopy: a living clinical practice guideline

2025· article· en· W4408904107 sur OpenAlexaff
Farid Foroutan, Per Olav Vandvik, Lise Mørkved Helsingen, Mette Kalager, Matt Rutter, Kevin Selby, Nastazja Pilonis, Joseph Anderson, Annette McKinnon, Jonathan Fuchs, Casey Quinlan, Maaike Buskermolen, Carlo Senore, Pu Wang, Joseph J.�Y. Sung, Ulrike Haug, Silje Bjerkelund, Κonstantinos Τriantafyllou, Dennis Shung, Natalie Halvorsen, Thomas McGinn, Tandekile Lubelwana Hafver, Valerie Reinthaler, Gordon Guyatt, Thomas Agoritsas, Shahnaz Sultan

Notice bibliographique

RevueBMJ · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueColorectal Cancer Screening and Detection
Établissements canadiensMcMaster UniversityImpactTed Rogers Centre for Heart ResearchUniversity Health Network
Organismes subventionnairesHORIZON EUROPE Framework ProgrammeEuropean Commission
Mots-clésColonoscopyMedicineGuidelineColorectal cancerIncidence (geometry)Context (archaeology)PerforationRandomized controlled trialCancerIntensive care medicineInternal medicinePathology

Résumé

récupéré en direct d'OpenAlex

Abstract Clinical question In adult patients undergoing colonoscopy for any indication (screening, surveillance, follow-up of positive faecal immunochemical testing, or gastrointestinal symptoms such as blood in the stools) what are the benefits and harms of computer-aided detection (CADe)? Context and current practice Colorectal cancer (CRC), the third most common cancer and the second leading cause of cancer-related death globally, typically arises from adenomatous polyps. Detection and removal of polyps during colonoscopy can reduce the risk of cancer. CADe systems use artificial intelligence (AI) to assist endoscopists by analysing real-time colonoscopy images to detect potential polyps. Despite their increasing use in clinical practice, guideline recommendations that carefully balance all patient-important outcomes remain unavailable. In this first iteration of a living guideline, we address the use of CADe at the level of an individual patient. Evidence Evidence for this recommendation is drawn from a living systematic review of 44 randomised controlled trials (RCTs) involving more than 30 000 participants and a companion microsimulation study simulating 10 year follow-up for 100 000 individuals aged 60-69 years to assess the impact of CADe on patient-important outcomes. While no direct evidence was found for critical outcomes of colorectal cancer incidence and post-colonoscopy cancer incidence, low certainty data from the trials indicate that CADe may increase positive endoscopy findings. The microsimulation modelling, however, suggests little to no effect on CRC incidence, CRC-related mortality, or colonoscopy-related complications (perforation and bleeding) over the 10 year follow-up period, although low certainty evidence indicates CADe may increase the number of colonoscopies performed per patient. A review of values and preferences identified that patients value mortality reduction and quality of care but worry about increased anxiety, overdiagnosis, and more frequent surveillance. Recommendation For adults who have agreed to undergo colonoscopy, we suggest against the routine use of CADe (weak recommendation). How this guideline was created An international panel, including three patient partners, 11 healthcare providers, and seven methodologists, deemed by MAGIC and The BMJ to have no relevant competing interests, developed this recommendation. For this guideline the panel took an individual patient approach. The panel started by defining the clinical question in PICO format, and prioritised outcomes including CRC incidence and mortality. Based on the linked systematic review and microsimulation study, the panel sought to balance the benefits, harms, and burdens of CADe and assumed patient preferences when making this recommendation Understanding the recommendation The guideline panel found the benefits of CADe on critical outcomes, such as CRC incidence and post-colonoscopy cancer incidence, over a 10 year follow up period to be highly uncertain. Low certainty evidence suggests little to no impact on CRC-related mortality, while the potential burdens—including more frequent surveillance colonoscopies—are likely to affect many patients. Given the small and uncertain benefits and the likelihood of burdens, the panel issued a weak recommendation against routine CADe use. The panel acknowledges the anticipated variability in values and preferences among patients and clinicians when considering these uncertain benefits and potential burdens. In healthcare settings where CADe is available, individual decision making may be appropriate. Updates This is the first iteration of a living practice guideline. The panel will update this living guideline if ongoing evidence surveillance identifies new CADe trial data that substantially alters our conclusions about CRC incidence, mortality, or burdens, or studies that increase our certainty in values and preferences of individual patients. Updates will provide recommendations on the use of CADe from a healthcare systems perspective (including resource use, acceptability, feasibility, and equity), as well as the combined use of CADe and computer aided diagnosis (CADx). Users can access the latest guideline version and supporting evidence on MAGICapp, with updates periodically published in The BMJ .

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,005
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,198
Score d'incertitude au seuil0,581

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,021
Tête enseignante GPT0,369
Écart entre enseignants0,348 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations34
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueBMJMême sujetColorectal Cancer Screening and DetectionTravaux en français237 207