Disabling and Reoperation in Patients with Crohn's Disease Subject to Early Surgery or Immunosuppression: A Bayesian Network Prognostic Model

Crohn's disease is one type of inflammatory bowel disease whose incidence is currently increasing, subject to relapse and disabling, with unknown etiology, and usually diagnosed between the second and third decade of life. The aim of this work is to develop a Bayesian network tool to predict disabling and reoperation in patients with Crohn's disease subject to early surgery or immunosuppressors intake. Multi-centric study data from patients with surgery or immunosuppression in the first six months after diagnosis was used, focusing on the prognosis and the analysis of factors' interaction. Patients were grouped by the index episode: immunosuppressors intake, and surgery (stratified considering the use or not of immunosuppressors 6 months after surgery). Patient group was associated with disease behavior, upper gastrointestinal tract location (L4) and age at diagnosis, while disease extent was associated to perianal disease. For disabling, association between perianal disease and gender and location was also found. Association between gender and L4 was also found for reoperation. The cross-validated discriminative power of the models were high for both disabling (above 70%) and reoperation (above 80%). The generated models presented interesting insights on factor interaction and predictive ability for the prognosis, supporting their use in future clinical decision support systems.