Risk Matrix for Prediction of Disease Progression in a Referral Cohort of Patients with Crohn's Disease.

Lakatos, Peter L and Sipeki, Nora and Kovacs, Gyorgy and Palyu, Eszter and Norman, Gary L and Shums, Zakera and Golovics, Petra A and Lovasz, Barbara D and Antal-Szalmas, Peter and Papp, Maria (2015) Risk Matrix for Prediction of Disease Progression in a Referral Cohort of Patients with Crohn's Disease. Journal of Crohn's & colitis. ISSN 1876-4479

Preview

Text ecco-jcc.jjv127.full (2).pdf Download (835kB) | Preview

Abstract

BACKGROUND Early identification of patients with Crohn's disease (CD) at risk of subsequent complications is essential for adapting the treatment strategy. We aimed to develop a prediction model including clinical and serological markers for assessing the probability of developing advanced disease in a prospective referral CD cohort. METHODS Two hundred and seventy-one consecutive CD patients (42.4% males, median follow-up 108 months) were included and followed up prospectively. Anti-Saccharomyces cerevisiae antibodies (ASCA IgA/IgG) were determined by enzyme-linked immunosorbent assay. The final analysis was limited to patients with inflammatory disease behaviour at diagnosis. The final definition of advanced disease outcome was having intestinal resection or disease behaviour progression. RESULTS Antibody (ASCA IgA and/or IgG) status, disease location and need for early azathioprine were included in a 3-, 5- and 7-year prediction matrix. The probability of advanced disease after 5 years varied from 6.2 to 55% depending on the combination of predictors. Similar findings were obtained in Kaplan-Meier analysis; the combination of ASCA, location and early use of azathioprine was associated with the probability of developing advanced disease (p < 0.001, log rank test). CONCLUSIONS Our prediction models identified substantial differences in the probability of developing advanced disease in the early disease course of CD. Markers identified in this referral cohort were different from those previously published in a population-based cohort, suggesting that different prediction models should be used in the referral setting.

Actions (login required)

Edit Item