A validated risk stratification tool for detecting high-risk small bowel Crohn's disease

Area of Science:

• Gastroenterology
• Diagnostic tools
• Inflammatory bowel disease

Background:

• Delays in diagnosing Crohn's disease (CD) are linked to ileal location and increased complication risk.
• Early recognition of ileal CD is essential for timely intervention and improved patient outcomes.

Purpose of the Study:

• To develop a simple risk assessment tool for primary care physicians (PCPs).
• To enable earlier identification of potential ileal CD, shortening the delay to specialist investigation.

Main Methods:

• Utilized three cohorts (totaling 187 ileal CD patients and 712 controls) for developing and validating a risk prediction algorithm.
• Acquired clinical symptoms and serological biomarkers to build the predictive model.
• Trained the algorithm independently on each cohort and tested it on the latter two.

Main Results:

• A risk prediction algorithm incorporating altered bowel habit, abdominal pain, white cell count, albumin, and platelet counts demonstrated high predictive accuracy (AUCs ranging from 0.92 to 0.96).
• The model was successfully validated across independent cohorts.
• C-reactive protein was associated with ileal CD but not significant in the multivariate model.

Conclusions:

• A web-based risk stratification tool for ileal CD has been developed.
• The tool utilizes objective and symptom-based criteria to aid PCPs in confidently requesting specialist assessment for high-risk patients.