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.
|Publication status||E-pub ahead of print - Sept 28 2017|
- Journal Article