Biomarker-Based Models Outperform Patient-Reported Scores in Predicting Endoscopic Inflammatory Disease Activity

Abstract

Background: The Crohn's Disease Activity Index (CDAI), a scoring index including patient-reported outcomes (PROs), has known limitations for measuring intestinal inflammatory disease burden. Noninvasive markers of inflammation could prove more accurate than PROs; thus, regulatory authorities are exploring the use of PROs and endoscopic data as coprimary end points in clinical trials. The aim of this study was to assess the predictive ability of individual components of the CDAI, along with biomarker concentrations, to create models for predicting endoscopic disease activity. Methods: Between 2004 and 2006, 164 patients with established Crohn's disease (CD) undergoing clinically indicated ileocolonoscopy were recruited. Individual CDAI variables and fecal calprotectin (FC) were selected to explore their predictive accuracy for endoscopic disease activity, with the Simple Endoscopic Score-Crohn's Disease (SES-CD) as the outcome variable. Simple Poisson regression was performed on each variable, and 2 multivariate models were created (PRO-exclusive and PRO+FC [PRO+]). Additional analyses explored the patient-level agreement between models. Results: Number of liquid stools, abdominal pain, hematocrit (Hct), FC, and high-sensitivity C-reactive protein (hsCRP) correlated significantly with the SES-CD. For the prediction of SES-CD (>7 vs <6), the area under the curve (AUC) was 0.81, with 63% and 88% sensitivity and specificity, for the PRO+ model, compared with a 0.56 AUC, with 61% and 55%, respectively, for the PRO model. Intra-individual comparison revealed the PRO+ model to be superior in the prediction of endoscopically active disease. Conclusions: The inclusion of biomarkers significantly improved predictive accuracy for endoscopic disease activity compared with PROexclusive models.