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Inflammatory Bowel Diseases:
doi: 10.1097/01.MIB.0000436956.78220.67
Original Clinical Articles

Risk Matrix for Prediction of Advanced Disease in a Population-based Study of Patients with Crohn's Disease (the IBSEN Study)

Solberg, Inger C. MD, PhD*; Cvancarova, Milada MSc, PhD; Vatn, Morten H. MD, PhD; Moum, Bjørn MD, PhD§

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Abstract

Background:

Identifying patients with Crohn's disease with increased risk of subsequent complications is essential for appropriate treatment. Based on exploratory analysis, we developed a prediction model for assessing the probability of developing advanced disease 5 and 10 years after diagnosis.

Methods:

A population-based cohort of 237 patients with Crohn's disease diagnosed from 1990–1994 was followed for 10 years. In the 5-year analysis, advanced disease was defined as having intestinal resection, progression in disease behavior, or need for thiopurines. The analysis was limited to patients with uncomplicated disease at diagnosis who were alive (n = 140), excluding those who were lost during follow-up (n = 8). For the 10-year analysis, advanced disease was defined as having surgery, excluding those who had surgery within the first 30 days (n = 7), those who died (n = 18), or were lost during follow-up (n = 22). Based on the best fitted multiple model, the probabilities of advanced disease were computed for selected baseline levels of the covariates and the results were arranged in a prediction matrix. Except for ASCA, all predictors were measured at diagnosis.

Results:

ASCA status, disease location, age, and need for systemic steroids were included in the 5-year prediction matrix. The probabilities of advanced disease during this period varied from 8.6% to 92.0% depending on the combination of predictors. The 10-year matrix combined ASCA status, disease behavior, age, and need for systemic steroids; the probabilities of advanced disease ranged from 12.4% to 96.7%.

Conclusions:

Our prediction models revealed substantial differences in the probability of developing advanced disease in the short and intermediate course of Crohn's disease, suggesting that a model-based prediction matrix is useful in early disease management.

Copyright © 2013 Crohn's & Colitis Foundation of America, Inc.

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