De Novo Crohn’s Disease in Children With Ulcerative Colitis Undergoing Ileal Pouch–Anal Anastomosis: A Multicenter, Retrospective Study From the Pediatric IBD Porto Group of the ESPGHAN

Abstract

Abstract Background and Aims We sought to define the prevalence and to characterize possible predictive factors of Crohn’s disease (CD) occurring in children with ulcerative colitis (UC) after ileal pouch–anal anastomosis (IPAA). Methods This was a multicenter, retrospective study including 15 centers of the Porto IBD group of the European Society for Pediatric Gastroenterology, Hepatology and Nutrition. Children with a confirmed diagnosis of UC undergoing colectomy with IPAA and a minimal follow up of 6 months were identified. The following data were collected: demographic data; endoscopic and histologic data; disease activity; laboratory exams; therapeutic history; indication for surgery, type, and timing; and IPAA functional outcomes and complications. In de novo CD cases, time of diagnosis, phenotype, location, and therapies were gathered. Results We identified 111 UC children undergoing IPAA from January 2008 to June 2018 (median age at colectomy: 13 years; age range: 1-18 years; female/male: 59/52). The median time from diagnosis to colectomy was 16 (range, 0-202) months. At the last follow-up, 40 (36%) of 111 children developed pouchitis. The criteria for de novo CD were met in 19(17.1%) of 111 children with a 25-month median (range, 3-61 months). At last follow-up, 12 (63.1%) of 19 were treated with biologics and in 5 (26.3%) of 19 children, the pouch was replaced with definitive ileostomy. In a multivariable logistic regression model, decreased preoperative body mass index z scores (odds ratio, 2.2; 95% confidence interval, 1.1-4.4; P = .01) resulted as the only variable associated with CD development. Conclusions Children with UC undergoing IPAA carry a high risk of developing subsequent CD. De novo CD cases showed decreased preoperative body mass index z scores, identifying a poor nutritional status as a possible predictive factor.