Endoscopy and central reading in inflammatory bowel disease clinical trials: achievements, challenges and future developments. Issue 2 (22nd July 2020)

• Record Type: Journal Article
• Authors: Gottlieb, Klaus; Daperno, Marco; Usiskin, Keith; Sands, Bruce E; Ahmad, Harris; Howden, Colin W; Karnes, William; Oh, Young S; Modesto, Irene; Marano, Colleen; Stidham, Ryan William; Reinisch, Walter
• Is Part Of: Gut. Volume 70:Issue 2(2021)
• Page Start: 418
• Page End: 426
• Publication Date: 2020-07-22
• Subjects: CLINICAL TRIALS -- INFLAMMATORY BOWEL DISEASE -- ENDOSCOPY; Gastroenterology -- Periodicals; 616.33
• DOI: 10.1136/gutjnl-2020-320690
• Languages: English
• ISSNs: 0017-5749

Abstract

Abstract : Central reading, that is, independent, off-site, blinded review or reading of imaging endpoints, has been identified as a crucial component in the conduct and analysis of inflammatory bowel disease clinical trials. Central reading is the final step in a workflow that has many parts, all of which can be improved. Furthermore, the best reading algorithm and the most intensive central reader training cannot make up for deficiencies in the acquisition stage (clinical trial endoscopy) or improve on the limitations of the underlying score (outcome instrument). In this review, academic and industry experts review scoring systems, and propose a theoretical framework for central reading that predicts when improvements in statistical power, affecting trial size and chances of success, can be expected: Multireader models can be conceptualised as statistical or non-statistical (social). Important organisational and operational factors, such as training and retraining of readers, optimal bowel preparation for colonoscopy, video quality, optimal or at least acceptable read duration times and other quality control matters, are addressed as well. The theory and practice of central reading and the conduct of endoscopy in clinical trials are interdisciplinary topics that should be of interest to many, regulators, clinical trial experts, gastroenterology societies and those in the academic community who endeavour to develop new scoring systems using traditional and machine learning approaches.