Development of a Novel Predictive Model for the Clinical Course of Crohn's Disease: Results from the CONNECT Study

Abstract

BACKGROUND: A considerable number of patients with Crohn's disease (CD) develop irreversible intestinal damage, although the early administration of immunomodulatory or biological therapies might prevent this. The aims of our study were to develop and validate a novel predictive model that can be used to predict the risk of surgical intervention in Korean patients with CD.

METHODS: The prognostic model was derived from the multicenter longitudinal CONNECT (CrOhn's disease cliNical NEtwork and CohorT) study cohort consisting of 1338 patients with CD, who were split into training and validation sets. The Korean Crohn's Disease Prediction (KCDP) model was developed with the training set data using the Cox proportional hazards model and multivariate analysis, and was then validated using the validation set.

RESULTS: A total of 1271 patients with CD were analyzed. During the follow-up period of 10,188 patient-years (median 7.1 yrs), 361 patients (28.4%) underwent CD-related surgery. Age at diagnosis, jejunal involvement, initial disease behavior, and perianal disease at diagnosis were associated with a poor prognosis and included in the KCDP model, which showed a modest discrimination ability with a Harrel's c-index of 0.731 at 5 years, and was well calibrated (Hosmer-Lemeshow χ = 8.230, P = 0.511).

CONCLUSIONS: This is the first validated surgery risk prediction model for Korean patients with CD; it provides accurate individualized estimates of the probability of surgery using clinical parameters collected at diagnosis. This model might guide appropriate patient selection for the early intensive treatment of CD.