A158 FINDINGS FROM A MULTIDISCIPLINARY DATABASE FOR PATIENTS WITH BARRETT'S ESOPHAGUS AND EARLY ESOPHAGEAL ADENOCARCINOMA
Notice bibliographique
Résumé
Abstract Background Previously, Barrett’s esophagus (BE) with high grade dysplasia (HGD) or neoplasia was treated with esophagectomy; however, recent guidelines support the use of endoscopic mucosal resection (EMR) for T1a esophageal adenocarcinoma (EAC) and potentially T1b EAC. Long term data for outcomes from EMR are lacking and these treatments are often provided with minimal collaboration between gastroenterologists and thoracic surgeons. Purpose Our primary aim was to describe the findings from our multidisciplinary database of patients with Barrett’s esophagus and EAC undergoing endoscopic treatment. Secondary aims were to compare the overall survival and recurrence-free survival of patients undergoing endoscopic resection to those undergoing esophagectomy. Method For the endoscopic resection cohort, a combined retrospective and prospective database was created containing demographic, clinical, and oncologic variables for patients undergoing endoscopic resection for early stage EAC from 2009 to 2021. For the esophagectomy cohort, a pre-existing retrospective database including patients undergoing esophagectomy for esophageal cancer from 2012 to 2018 at a single institution was used. A multivariate cox proportional hazards model was developed for recurrence-free survival and overall survival using a hypothesis driven approach. A kaplan-meier (KM) curve with associated log-rank test was created to evaluate recurrence-free survival and overall survival stratified by treatment modality. Result(s) A total of 108 patients were included in the analysis (73 EMR, 35 esophagectomy). Baseline characteristics including age, sex, and co-morbidities were similar among the two groups. KM curves stratified by treatment modality are provided in Figure 1. Esophagectomy was associated with greater DFS on univariate log-rank test (p = 0.0127), but no difference in OS (p = 0.9306). There was no significant difference between esophagectomy and endoscopic resection in the cox-model for OS (HR 1.03, 95% CI 0.45-2.32, p = 0.914). Endoscopic resection was associated with increased hazards of disease recurrence in the cox model for DFS (HR 2.56, 95% CI 1.1-6.0, p = 0.032). In the logistic regression model, high grade disease (OR 5.43, 95% CI 1.1 – 26.1, p = 0.035) and submucosal involvement (OR 7.8, 1.9-31.4, p = 0.004) were identified as significant predictors of positive margin necessitating esophagectomy after initial endoscopic resection. All patients who experienced a positive margin after endoscopic therapy were evaluated by a thoracic surgeon and proceeded to esophagectomy. Conclusion(s) In this largely retrospective analysis, our multidisciplinary approach was shown to be highly efficacious in the treatment of BE with EAC. Through optimizing collaboration between thoracic surgeons and gastroenterologists, patients receive the best therapeutic approach for their unique condition, taking into account oncologic factors and clinical comorbidities. 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 | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,000 | 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 ».