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International development and validation of a classification system for the identification of Barrett’s neoplasia using acetic acid chromoendoscopy: the Portsmouth acetic acid classification (PREDICT)

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Background - Barrett’s oesophagus is an established risk factor for developing oesophageal adenocarcinoma. However, Barrett’s neoplasia can be subtle and difficult to identify. Acetic acid chromoendoscopy (AAC) is a simple technique that has been demonstrated to highlight neoplastic areas but lesion recognition with AAC remains a challenge, thereby hampering its widespread use.

    Objective - To develop and validate a simple classification system to identify Barrett’s neoplasia using AAC.

    Design - The study was conducted in four phases: phase 1—development of component descriptive criteria; phase 2—development of a classification system; phase 3—validation of the classification system by endoscopists; and phase 4—validation of the classification system by non-endoscopists.

    Results - Phases 1 and 2 led to the development of a simplified AAC classification system based on two criteria: focal loss of acetowhitening and surface patterns of Barrett’s mucosa. In phase 3, the application of PREDICT (Portsmouth acetic acid classification) by endoscopists improved the sensitivity and negative predictive value (NPV) from 79.3% and 80.2% to 98.1% and 97.4%, respectively (p<0.001). In phase 4, the application of PREDICT by non-endoscopists improved the sensitivity and NPV from 69.6% and 75.5% to 95.9% and 96.0%, respectively (p<0.001).

    Conclusion - We developed and validated a classification system known as PREDICT for the diagnosis of Barrett’s neoplasia using AAC. The improvement seen in the sensitivity and NPV for detection of Barrett’s neoplasia in phase 3 demonstrates the clinical value of PREDICT and the similar improvement seen among non-endoscopists demonstrates the potential for generalisation of PREDICT once proven in real time.
    Original languageEnglish
    Pages (from-to)2085-2091
    JournalGut
    Volume67
    Issue number12
    Early online date28 Sept 2017
    DOIs
    Publication statusPublished - 9 Nov 2018

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 17 - Partnerships for the Goals
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