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Review
. 2016 Jan 21;22(3):1017-33.
doi: 10.3748/wjg.v22.i3.1017.

How to predict clinical relapse in inflammatory bowel disease patients

Elisa Liverani  1 , Eleonora Scaioli  1 , Richard John Digby  1 , Matteo Bellanova  1 , Andrea Belluzzi  1
Affiliations
Review

How to predict clinical relapse in inflammatory bowel disease patients

Elisa Liverani et al. World J Gastroenterol. .

Abstract

Inflammatory bowel diseases have a natural course characterized by alternating periods of remission and relapse. Disease flares occur in a random way and are currently unpredictable for the most part. Predictors of benign or unfavourable clinical course are required to facilitate treatment decisions and to avoid overtreatment. The present article provides a literature review of the current evidence on the main clinical, genetic, endoscopic, histologic, serologic and fecal markers to predict aggressiveness of inflammatory bowel disease and discuss their prognostic role, both in Crohn's disease and ulcerative colitis. No single marker seems to be reliable alone as a flare predictor, even in light of promising evidence regarding the role of fecal markers, in particular fecal calprotectin, which has reported good results recently. In order to improve our daily clinical practice, validated prognostic scores should be elaborated, integrating clinical and biological markers of prognosis. Finally, we propose an algorithm considering clinical history and biological markers to intercept patients with high risk of clinical relapse.

Keywords: Clinical predictors; Clinical relapse; Crohn’s disease; Fecal calprotectin; Ulcerative colitis.

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Figures

Figure 2
Figure 2
Algorithm to identify Crohn’s disease patients with high risk of clinical relapse. 1In at least 2 determinations. CRP: C reactive protein; FC: Fecal calprotectin.
Figure 3
Figure 3
Algorithm to identify ulcerative colitis patients with high risk of clinical relapse. 1In at least 2 determinations. FC: Fecal calprotectin.
Figure 1
Figure 1
“Probing items” available for the clinicians to predict clinical relapse in inflammatory bowel diseases.
See this image and copyright information in PMC

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MeSH terms