A156 OUTCOMES FOLLOWING ENDOSCOPIC RESECTION OF GASTRIC NEUROENDOCRINE TUMOURS FROM A TERTIARY-CARE ACADEMIC CENTRE
Notice bibliographique
Résumé
Abstract Background Gastric neuroendocrine tumours (G-NET) are rare cancers derived from neuroendocrine cells of the stomach. A steady increase in the incidence of these tumours has been observed. Current treatment and surveillance strategies are guided by various tumour characteristics including size, grade, and depth of invasion. There exists conflicting evidence, however, on the rates of recurrence from positive resection margins following primary endoscopic resection. Thus, it remains uncertain whether complete endoscopic resection (R0) of these indolent tumours is clinically significant and whether follow-up endoscopic or surgical intervention is justified. Purpose Our aim is to characterize current management patterns and clinical outcomes in patients undergoing endoscopic resection of G-NETs. Method We conducted a retrospective, single-centre cohort study at The Centre for Advanced Therapeutic Endoscopy and Endoscopic Oncology at St. Michael’s Hospital, Toronto, Ontario. Consecutive patients over the age of 18 who underwent endoscopic resection of histologically proven G-NETs between 2011 and 2020 were included. Data on patient, endoscopic, and tumour characteristics were collected through electronic chart review. Descriptive statistics were conducted for data analysis. Result(s) A total of 155 foregut neuroendocrine tumours were endoscopically resected during the study period, of which 108 were identified as G-NETs. 95.3% were classified as Type I. Mean tumour size was 8.93 ± 5.27 mm. Cap-assisted EMR was performed most frequently (n=51), followed by conventional EMR (n=35). ESD was performed in eight cases. Seven intra-procedural perforations occurred, of which all were closed endoscopically. One patient experienced post-procedural perforation requiring ICU and surgery. Positive resection margins (R1) were found in 25% of cases (n=27), of which 78% were assessed at surveillance endoscopy 1 (SE1). Six patients with R1 margins were referred for surgical evaluation and four were lost to follow-up. 78% of all resected G-NETs were followed at SE1 with a median interval of 196 days (range, 23 to 3373). SE1 recurrence rate at the primary resection site was 14% (n=12), of which two were from routine scar biopsies in the absence of endoscopically identifiable recurrence. All visible recurrences at these sites (n=10) were managed with repeat endoscopic resection. Patient and tumour characteristics in the evaluation of G-NET recurrence are presented in Table I. Image Conclusion(s) G-NET recurrence occurs in less than 15% of patients at surveillance endoscopy following endoscopic resection in spite of a predictably higher R1 resection rate. Patient, endoscopic, and tumour factors including method of resection and margin status do not appear to impact the development of early recurrence. Given the indolent nature of these tumours, patients with positive resection margins can be followed conservatively. Further investigation is warranted to determine the optimal duration and surveillance strategy for these patients. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».