Analysis of biomarkers and composite scores in IBD patients using probabilistic fuzzy systems

The incidence of inflammatory bowel disease (IBD) is rising worldwide. Preventing disease progression by tight monitoring of disease activity using non-invasive procedures is important to prevent disease progression. In literature composite scores, combining biomarkers and clinical activity scores, have been described which aim to detect disease activity. In this paper we analyze the components of these composite scores in a data-driven manner using probabilistic fuzzy system (PFS).In this paper, we define a specific PFS for the analysis of the relationship between the biomarker fecal calprotectin (FC), with biomarkers erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) and clinical activity scores for two disease phenotypes, namely Crohn’s disease and ulcerative colitis.We report the relations between these biomarkers and clinical activity scores using the proposed PFS, and show how the statistical properties of FC indicator relates to the remaining biomarkers and clinical activity scores. Furthermore, we related the findings on the clinical activity scores to the conventional thresholds used in the literature to define susceptibility of disease activity to support clinical interpretation of results. The results show that analyzing the recently available data using PFS lead to valuable information for detecting IBD disease activity where most conventional thresholds for disease indicators are in line with the data-based findings.