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. 2023;41(6):879-889.
doi: 10.1159/000531789. Epub 2023 Aug 23.

The Risk of Developing Disabling Crohn's Disease: Validation of a Clinical Prediction Rule to Improve Treatment Decision Making

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The Risk of Developing Disabling Crohn's Disease: Validation of a Clinical Prediction Rule to Improve Treatment Decision Making

Guillermo Bastida Paz et al. Dig Dis. 2023.

Abstract

Background: Crohn's disease (CD) is characterized by the development of complications over the course of the disease. It is crucial to identify predictive factors of disabling disease, in order to target patients for early intervention. We evaluated risk factors of disabling CD and developed a prognostic model.

Methods: In total, 511 CD patients were retrospectively analyzed. Univariate and multivariate logistic regression analyses were used to identify demographic, clinical, and biological risk factors. A predictive nomogram model was developed in a subgroup of patients with noncomplicated CD (inflammatory pattern and no perianal disease).

Results: The rate of disabling CD within 5 years after diagnosis was 74.6%. Disabling disease was associated with gender, location of disease, requirement of steroids for the first flare, and perianal lesions. In the subgroup of patients (310) with noncomplicated CD, the rate of disabling CD was 80%. In the multivariate analysis age at onset <40 years (OR = 3.46, 95% confidence interval [CI] = 1.52-7.90), extensive disease (L3/L4) (OR = 2.67, 95% CI = 1.18-6.06), smoking habit (OR = 2.09, 95% CI = 1.03-4.27), requirement of steroids at the first flare (OR = 2.20, 95% CI = 1.09-4.45), and albumin (OR = 0.59, 95% CI = 0.36-0.96) were associated with development of disabling disease. The developed predictive nomogram based on these factors presented good discrimination, with an area under the receiver operating characteristic curve of 0.723 (95% CI: 0.670-0.830).

Conclusion: We identified predictive factors of disabling CD and developed an easy-to-use prognostic model that may be used in clinical practice to help identify patients at high risk and address treatment effectively.

Keywords: Biomarkers; Crohn’s disease; Natural history; Personalized medicine; Predictive factors; Risk factors.

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