Journal Article

Biomarker risk stratification with capsule sponge in the surveillance of Barrett's oesophagus: prospective evaluation of UK real-world implementation

Hill, Catherine, Mainie, Inder, Ross-Innes, Caryn S, Boyle, Ita, Nutzinger, Barbara, Shaw, Kim, Debiram-Beecham, Irene, Kerridge, Abigail, Morris, Danielle, Wu, Lianlian, Gogin, Nicola, Modolell, Ines, O'Donovan, Maria, Somerset, Timothy, Markert, Greta, Bisschops, Daan, Lovat, Laurence, Askinyte, Victoria, Graham, David, McGoran, John, Vickery, Craig, Tan, W Keith, di Pietro, Massimiliano, Turkington, Richard, Harvey, Jacquelyn, Harrison, Jon, Warburton, Samantha, Markowetz, Florian, Grehan, Nicola, Hadjinicolaou, Andreas V, Sehgal, Vinay, Caspillo, Evelyn, Ortiz-Fernandez-Sordo, Jacobo, Sasieni, Peter, Fitzgerald, Rebecca C, Johnston, David N., Bellou, Marianna, Sweis, Rami, Dhar, Anjan, Evans, Tara, Prew, William

2025

Overview

Endoscopic surveillance is the clinical standard for Barrett's oesophagus, but its effectiveness is inconsistent. We have developed a test comprising a pan-oesophageal cell collection device coupled with biomarkers to stratify patients into three risk groups. We aimed to prospectively evaluate the prespecified risk stratification tool to establish whether it can identify those at highest risk of dysplasia or cancer to prioritise the timing of endoscopy; and safely be used to follow up the low-risk group, thus sparing patients from unnecessary endoscopies. Participants were recruited as part of two multicentre, prospective, pragmatic implementation studies from 13 hospitals in the UK. Patients with non-dysplastic Barrett's oesophagus had a capsule-sponge test which was assessed in an ISO-accredited laboratory. Patients were included if they were aged at least 18 years with a non-dysplastic Barrett's oesophagus diagnosis at their last endoscopy who were undergoing surveillance according to the published UK guidelines. Patients were assigned as low (clinical and capsule-sponge biomarkers negative), moderate (negative for capsule-sponge biomarkers, positive clinical biomarkers—age, sex, and segment length), or high risk (p53 abnormality or glandular atypia regardless of clinical biomarkers, or both). The primary outcome was a diagnosis of high-grade dysplasia or cancer necessitating treatment, according to the risk group assignment. 910 patients recruited between August, 2020, and December, 2024 participated, of whom 138 (15%) were classified as high risk, 283 (31%) moderate risk and 489 (54%) low risk. The positive predictive value for any dysplasia or worse in the high-risk group was 37·7% (95% CI 29·7–46·4). Patients with both atypia and aberrant p53 had the highest risk of high-grade dysplasia or cancer (relative risk 135·8 [95% CI 32·7–564·0] relative to the low-risk group). The prevalence of high-grade dysplasia or cancer in the low-risk group was 0·4% (95% CI 0·1–1·6); the negative predictive value for any dysplasia or cancer was 97·8% (95% CI 95·9–98·8). Applying a machine learning algorithm as part of a digital-pathology workflow reduces the proportion needing p53 pathology review to 32% without missing any positive cases. The risk-panel substantially enriches for dysplasia and capsule-sponge-based surveillance could be used in low-risk Barrett's oesophagus in lieu of endoscopy. Innovate UK, Cancer Research UK, National Health Service England Cancer Alliance.

• Publisher: Elsevier Ltd,Elsevier Limited
• Subject: Adenocarcinoma - diagnosis / Aged / Barrett Esophagus - diagnosis / Barrett Esophagus - pathology / Barrett's esophagus / Biomarkers / Biomarkers - analysis / Cancer / Cancer therapies / Capsule Endoscopy / Diagnosis / Dysplasia / Early Detection of Cancer - methods / Endoscopy / Esophageal cancer / Esophageal Neoplasms - diagnosis / Esophageal Neoplasms - pathology / Esophagoscopy / Evaluation / Female / Humans / Machine learning / Male / Middle Aged / p53 Protein / Pathology / Patients / Primary care / Prospective Studies / Risk / Risk Assessment - methods / Risk groups / Surveillance / United Kingdom - epidemiology