Meta-Analytic Bayesian Model For Differentiating Intestinal Tuberculosis from Crohn's Disease

Abstract

Objectives Distinguishing intestinal tuberculosis (ITB) from Crohn's disease (CD) is difficult, although studies have reported clinical, endoscopic, imaging, and laboratory findings that help to differentiate these two diseases. We aimed to produce estimates of the predictive power of these findings and construct a comprehensive model to predict the probability of ITB vs. CD. Methods A systematic literature search for studies differentiating ITB from CD was conducted in MEDLINE, PUBMED, and EMBASE from inception until September 2015. Fifty-five distinct meta-analyses were performed to estimate the odds ratio of each predictive finding. Estimates with a significant difference between CD and ITB and low to moderate heterogeneity (I2 <50%) were incorporated into a Bayesian prediction model incorporating the local pretest probability. Results Thirty-eight studies comprising 2,117 CD and 1,589 ITB patients were included in the analyses. Findings in the model that significantly favored CD included male gender, hematochezia, perianal disease, intestinal obstruction, and extraintestinal manifestations; endoscopic findings of longitudinal ulcers, cobblestone appearance, luminal stricture, mucosal bridge, and rectal involvement; pathological findings of focally enhanced colitis; and computed tomographic enterography (CTE) findings of asymmetrical wall thickening, intestinal wall stratification, comb sign, and fibrofatty proliferation. Findings that significantly favored ITB included fever, night sweats, lung involvement, and ascites; endoscopic findings of transverse ulcers, patulous ileocecal valve, and cecal involvement; pathological findings of confluent or submucosal granulomas, lymphocyte cuffing, and ulcers lined by histiocytes; a CTE finding of short segmental involvement; and a positive interferon-γ release assay. The model was validated by gender, clinical manifestations, endoscopic, and pathological findings in 49 patients (27 CD, 22 ITB). The sensitivity, specificity, and accuracy for diagnosis of ITB were 90.9%, 92.6%, and 91.8%, respectively. Conclusions A Bayesian model based on the meta-analytic results is presented to estimate the probability of ITB and CD calibrated to local prevalence. This model can be applied to patients using a publicly available web application.

Differentiating Crohn’s disease from intestinal tuberculosis at presentation in patients with tissue granulomas

“…[8] The differentiation of ITB from CD is even more challenging in patients with histological evidence of non-caseating granulomas, as this further heightens the suspicion of ITB. [3] Patients with ITB are significantly more likely to have non-caseating granulomas than those with CD. [1,3] This was highlighted in a recent meta-analysis of 38 studies differentiating CD from ITB.…”

“…[3] Patients with ITB are significantly more likely to have non-caseating granulomas than those with CD. [1,3] This was highlighted in a recent meta-analysis of 38 studies differentiating CD from ITB. There were 2 117 cases of CD and 1 589 cases of ITB.…”

“…In this analysis, the presence of granulomas was significantly associated with a diagnosis of ITB. [3] Ours is the first study with the objective of identifying factors differentiating ITB from CD in exclusively granuloma-positive patients. Several factors were identified as being valuable in this regard.…”

“…This is in concordance with reports from several cohort studies, as well as the formerly mentioned Bayesian model. [3,9] The commonest EIM in CD was IDA. This finding is not unexpected, as it is the most common systemic complication of CD.…”

“…[3] To date, no study has been done in this particular subgroup to analyse factors that could aid in this diagnostic dilemma.…”