Parambir S. Dulai, MBBS, from the University of California San Diego in San Diego, California, USA discusses this review article “Assessment of mucosal healing in inflammatory bowel disease: review.”
Within this review article we have compared diagnostic tools currently available for the assessment of mucosal healing in inflammatory bowel disease, and we have outlined the ideal approach to integrating these tools into clinical trials and clinical practice.
Mucosal healing has become an important treatment target in inflammatory bowel disease and achieving complete mucosal healing has been associated with substantial reductions in short (symptom activity, steroid withdrawal), and long-term (hospitalization, surgery, colon cancer) disease related complications. The incorporation of this outcome in routine practice is growing, but It can be difficult at times for providers to understand the advantages, disadvantages, and considerations to be made when using and interpreting these tools. This may lead to inefficient monitoring of disease activity which carries implications on the impact the disease may have on patient outcomes and health care resource utilization.
Endoscopy remains the gold standard for disease assessment but the use of non-invasive tools (i.e. MRI) is likely to increase over time, particularly in patients with endoscopically inaccessible inflammation. Providers should be cautioned, however, that the presence of mucosal lesions cannot be reliably excluded based on cross sectional imaging alone, and further small-bowel endoscopy should be considered in all symptomatic patients. Video capsule endoscopy or device-assisted enteroscopy can be used, with device-assisted enteroscopy being preferred in stricturing Crohn’s disease because of the risk of capsule retention or in patients in whom small-bowel malignancy is a possibility. Ultimately, irrespective of the diagnostic tool used, it is the frequent repeated assessment over time with changes in therapy until mucosal healing is achieved that remains the cornerstone of a treat to target algorithm.
Read the abstract for this article online.
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