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Updated: Apr 27, 2026

qPCR Is a Sensitive and Rapid Method for Detection of Cytomegaloviral DNA in Formalin-fixed, Paraffin-embedded Biopsy Tissue
Published on: July 9, 2014
A model for identifying cytomegalovirus in patients with inflammatory bowel disease
Jeffrey D McCurdy1, Andrea Jones2, Felicity T Enders3
1Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
Background & Aims:
The presentation of cytomegalovirus (CMV) disease in patients with inflammatory bowel disease (IBD) can be similar to that of idiopathic IBD. It is a challenge to identify patients at highest risk for CMV. We investigated risk factors and generated a clinical score to identify patients with IBD at highest risk for CMV disease.
Methods:
We performed a retrospective case-control study of 68 patients with IBD (66% with ulcerative colitis, 31% with Crohn's disease, and 3% with unclassified IBD) diagnosed with CMV disease on the basis of tissue analysis from January 2005 through December 2011 at Mayo Clinic, Rochester. The patients were each matched with 3 patients with IBD and suspected CMV disease (controls). An a priori set of the most objective variables was used to create a model to identify those with CMV disease. Scores were assigned to each significant factor from the multivariable analysis. Cutoff values that identified patients with CMV with ≥85% sensitivity and specificity were selected.
Results:
Patients with medically refractory IBD (odds ratio [OR], 3.69; P < .001) or endoscopic ulcers (OR, 3.06; P < .001) and those treated with corticosteroids (OR, 2.95; P < .001) or immunomodulators (OR, 1.86; P = .030) but not tumor necrosis factor antagonists (OR, 1.30; P = .376) were more likely to have CMV disease than patients with IBD without these features. In a multivariable model, refractory disease, treatment with immunomodulators, and age older than 30 years were independently associated with CMV disease. Use of tumor necrosis factor antagonists was an insignificant factor even after adjustment.
Conclusions:
Clinical features can identify patients with IBD at risk for CMV disease. This model may help clinicians stratify patients on the basis of risk when CMV disease is suspected.
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