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INTRODUCTION: Minimally invasive endoscopic options are safe and effective alternatives to surgery for the treatment of symptomatic Zenker's diverticulum (ZD). However, there is no consensus on the gold-standard approach. We compared the safety and efficacy of Zenker's peroral endoscopic myotomy (Z-POEM), flexible diverticulotomy (FD), and rigid diverticulotomy (RD) for the management of ZD. METHODS: Patients undergoing treatment for ZD at three UK tertiary referral centres were identified and analysed between 2013 and 2023. Patient demographics, procedural details, clinical success, and 30-day adverse events (AE) were recorded. The primary outcomes were technical and clinical success defined as a fall in Dakkak and Bennett dysphagia score to ≤ 1 without re-intervention. RESULTS: There was no difference in baseline characteristics amongst 126 patients undergoing intervention (50 RD, 31 FD, 45 Z-POEM). Technical success for RD, FD, and Z-POEM was 80%, 100%, and 100%, respectively (p < 0.001). Over a mean follow-up of 11.0 months (95% CI 8.2-13.9), clinical success amongst those treated was 85.3% (RD), 74.1% (FD), and 83.7% (Z-POEM; p = 0.48) with recurrence in 17.2% (RD), 20.0% (FD), and 8.3% (Z-POEM; p = 0.50). AEs were equivalent between groups (p = 0.98). During this time, 11 patients underwent surgical myotomy with low clinical success (36.4%) and high morbidity. CONCLUSION: Endoscopic options for the treatment of ZD show equivalent rates of success, but failed RD often led to open myotomy with worse outcomes. Flexible endoscopic modalities are both safe and highly effective treatments that may be considered first-line in experienced centres and should be offered before surgery.
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Background: Salivary epigenetic biomarkers may detect esophageal cancer. Methods: A total of 256 saliva samples from esophageal adenocarcinoma patients and matched volunteers were analyzed with Illumina EPIC methylation arrays. Three datasets were created, using 64% for discovery, 16% for testing and 20% for validation. Modules of gene-based methylation probes were created using weighted gene coexpression network analysis. Module significance to disease and gene importance to module were determined and a random forest classifier generated using best-scoring gene-related epigenetic probes. A cost-sensitive wrapper algorithm maximized cancer diagnosis. Results: Using age, sex and seven probes, esophageal adenocarcinoma was detected with area under the curve of 0.72 in discovery, 0.73 in testing and 0.75 in validation datasets. Cancer sensitivity was 88% with specificity of 31%. Conclusion: We have demonstrated a potentially clinically viable classifier of esophageal cancer based on saliva methylation.