A Risk Matrix Model for the Prediction of Intestinal Tuberculosis and Differentiation from Crohn’s Disease

Background: Intestinal Tuberculosis (ITB) can be difficult to distinguish from Crohn’s Disease (CD), especially in resource-limited areas. By combining independent risk factors measured at diagnosis, we aimed to construct a visual risk matrix model that could predict ITB. Methods: Treatment naïve patients with ITB (n=38) and CD (n=37) were prospectively recruited from routine clinical practice in four Indian medical centres between October 2009 and July 2012.Records from case histories, clinical examination, endoscopy and histopathology of biopsies were collected prior to sampling for faecal- and serum calprotectin and C-reactive protein. Patients with malignancy, human immunodeficiency virus infection or age below 18 years were excluded from the study. Risk factors associated with ITB and CD diagnoses were identified from univariate analysis and entered into multiple models. The probabilities of ITB diagnosis were calculated for selected levels of risk factors and the results were arranged in a prediction matrix. Results: Four variables were significantly associated with ITB or CD diagnosis and were combined in the final matrix. Predictors of ITB were weight loss, mucosal nodularity and faecal calprotectin = 200μg/g; predictors of CD were multi-segment involvement and faecal calprotectin < 200μg/g. The probability of ITB at diagnosis ranged from 19 to 91% and for CD from 9 to 81%, depending of the level of the risk factors. Conclusion: A visual matrix model in which faecal calprotectin is combined with clinical and endoscopic risk factors could become a rapid, easy and pointof- care tool to differentiate between ITB and CD in clinics with limited resources.