Long-term classification stability and treatment patterns of inflammatory bowel disease unclassified: a longitudinal observational study.

Abstract

OBJECTIVE: In patients presenting with inflammatory bowel disease (IBD), it may not be possible to diagnose ulcerative colitis (UC) or Crohn's disease (CD) and a classification of IBD Unclassified (IBD-U) is applied. We aim to describe the long-term natural history and treatment patterns in IBD-U.

METHODS: This analysis was based on the Leeds IBD Steroid Study, a large retrospective study conducted at Leeds Teaching Hospitals (a UK-based tertiary IBD unit) that included all adult patients with an established diagnosis of IBD who had contact with the service between January 2016 and December 2017 and where access to primary care records were linked to hospital electronic records. Patients with IBD-U were analysed retrospectively. Baseline demographics and treatment patterns of patients with IBD-U were compared with UC and CD. Longitudinal follow-up occurred until 2025 to determine stability of IBD-U diagnosis.

RESULTS: Of 153 patients with IBD-U, 52% were male; the mean age was 46.6 years, and the mean disease duration was 13.1 years. Patients with IBD-U were less likely to receive mesalazine (85%) compared with UC (92%, p=0.0058) but more likely than patients with CD (44%, p<0.0001). Biologics were more often used for IBD-U (21%) than UC (9.5%, p<0.0001) but less often than CD (51%, p<0.0001). Steroid use and use of healthcare resources were higher in IBD-U than in UC and CD. 12 patients (7.8%) were reclassified as UC, 6 patients (3.9%) were reclassified as CD and 135 patients (88.2%) remained classified as IBD-U at the end of follow-up.

CONCLUSION: IBD-U remains largely a stable diagnosis over long-term follow-up. Patients with IBD-U exhibit distinct therapeutic patterns and increased healthcare utilisation compared with UC and CD. These findings underscore the clinical relevance of IBD-U as a persistent phenotype and highlight the need to optimise treatment decisions and reduce the burden associated with diagnostic uncertainty.