Turner, Dan

Abstract Background & Aims Central reading of endoscopy and histopathology is the current standard for disease activity assessment in inflammatory bowel disease (IBD) clinical trials but is limited by interreader and intrareader variability, operational delays, and cost. Artificial intelligence (AI) and machine learning (ML) offer the potential to improve accuracy, efficiency, and reproducibility. The International Organization for the Study of IBD (IOIBD) developed consensus statements on AI/ML use for endoscopic and histologic endpoint assessment in IBD trials. Methods As part of the IOIBD endpoints cluster initiative, a narrative, evidence-informed review with literature searches of Medline and Embase (January 2018-February 2025) identified studies applying AI/ML to endoscopy or histology in IBD. Relevant evidence informed 36 survey statements formulated by a steering committee. Seventy-two IOIBD members were invited to vote online; consensus required ≥80% agreement (score: 7-10 on a 10-point scale). Results Forty-five members completed the survey. Consensus was reached for 28 statements related to endoscopy, pathology, and trial design. Experts agreed that AI-based central reading could improve diagnostic accuracy, expedite processes, reduce costs, and enhance reproducibility. Combining human and AI assessments was favored over AI replacement. The key limitations identified included insufficient validation, generalizability concerns, and dependence on human-annotated training datasets. Conclusions This IOIBD consensus supports the integration of AI/ML into central reading for IBD clinical trials to improve objectivity, efficiency, and consistency, while maintaining human oversight. Further research should address validation, regulatory frameworks, and multimodal integration to enable broader adoption in both trials and clinical practice.

Abstract During the 20th century, inflammatory bowel disease (IBD) was considered a disease of early-industrialized regions in North America, Europe, and Oceania. At the turn of the 21st century, incidence of IBD increased in newly-industrialized and emerging regions in Africa, Asia, and Latin America, while prevalence in early-industrialized regions started to grow steadily. Changes in incidence and prevalence denote evolution of IBD across four epidemiologic stages: Stage 1 (Emergence), characterized by low incidence and prevalence; stage 2 (Acceleration in Incidence), characterized by rapidly rising incidence and low prevalence; and stage 3 (Compounding Prevalence), characterized by decelerating, plateauing, or declining incidence and steadily rising prevalence. A fourth stage (Prevalence Equilibrium) has been proposed where the slope of prevalence plateaus due to shifting demographics of an aging IBD population, but it has not yet been evidenced. To date, these stages have been theoretical without specific incidence/prevalence indicators defining transition points. Using real-world data from 490 population-based studies comprising 80 global regions and spanning over a century (1920–2023), we show spatiotemporal transitions across stages 1–3 and model transition towards stage 4. Understanding the evolution of IBD across epidemiologic stages allows healthcare systems to better prepare for the future worldwide burden of IBD.

Introduction The optimal trial design for assessing novel therapies in paediatric IBD (PIBD) is a subject of intense ongoing global discussions and debate among the different stakeholders. However, there is a consensus that the current situation in which most medications used in children with IBD are prescribed as off-label without sufficient paediatric data is unacceptable. Shortening the time lag between adult and paediatric approval of drugs is of the upmost importance. In this position paper we aimed to provide guidance from the global clinical research network (Pediatric Inflammatory Bowel Disease Network, PIBDnet) for designing clinical trials in PIBD in order to facilitate drug approval for children. Methods A writing group has been established by PIBDnet and topics were assigned to different members. After an iterative process of revisions among the writing group and one face-to-face meeting, all statements have reached consensus of >80% as defined a priori. Next, all core members of PIBDnet voted on the statements, reaching consensus of >80% on all statements. Comments from the members were incorporated in the text. Results The commentary includes 18 statements for guiding data extrapolation from adults, eligibility criteria to PIBD trials, use of placebo, dosing, endpoints and recommendations for feasible trials. Controversial issues have been highlighted in the text. Conclusion The viewpoints expressed in this paper could assist planning clinical trials in PIBD which are both of high quality and ethical, while remaining pragmatic.