https://orcid.org/0000-0001-7800-1984
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Ohad Atia, Dan Turner, Letter: Predictors of Complicated Disease Course in Children and Adults With Ulcerative Colitis—Authors’ Reply, Inflammatory Bowel Diseases, 2025;, izaf071, https://doi.org/10.1093/ibd/izaf071
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Dear Editors,
We are grateful for the thoughtful comments made by Ye et al. and the opportunity to further clarify our study on predictors of disease course in children and adults with ulcerative colitis (UC) using the Israeli-Inflammatory Bowel Diseases Research Nucleus (epi-IIRN) nationwide cohort.1 While prospective cohorts or registries typically have granular data available including disease extent, endoscopic severity, clinical indices, and biomarkers,2 administrative studies lack detailed data but are based on large, unselected populations with long-term follow-up. The latter is particularly useful when attempting to predict uncommon outcomes, such as colectomy in UC. The large sample size of our nationwide cohort had enough power to cluster blood tests into an integrative prediction model. Prospective cohort studies provide invaluable insights by allowing detailed, hypothesis-driven investigations into disease mechanisms and treatment responses. These are typically collected from referral inflammatory bowel disease centers, including small and selected cohorts, without some mild cases followed in the community. As a result, predictive models derived from cohort studies with multiple potential predictors are prone to overfitting and type I errors.3,4 Nonetheless, they may highlight possible predictors to be explored further in replication or unselected cohorts. Therefore, the study designs should be viewed as complementary, with strengths and weaknesses to each. Future research could attempt to add granular variables to the blood test results–based prediction rule, such as endoscopic and clinical indices. Even without adding more granular data, our study paves the way for the development of automated systems that can alert gastroenterologists to patients at risk for severe disease based on blood tests collected routinely as part of clinical care.
