Identification of Pediatric Patients With Celiac Disease Based on Serology and a Classification and Regression Tree Analysis

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Celiac disease is detected using serology and endoscopy analyses. We used multiple statistical analyses of a geographically isolated population in the United States to determine whether a single serum screening can identify individuals with celiac disease.


We performed a retrospective study of 3555 pediatric patients (18 years old or younger) in the intermountain West region of the United States from January 1, 2008, through September 30, 2013. All patients had undergone serologic analyses for celiac disease, including measurement of antibodies to tissue transglutaminase (TTG) and/or deamidated gliadin peptide (DGP), and had duodenal biopsies collected within the following year. Modified Marsh criteria were used to identify patients with celiac disease. We developed models to identify patients with celiac disease using logistic regression and classification and regression tree (CART) analysis.


Single use of a test for serum level of IgA against TTG identified patients with celiac disease with 90% sensitivity, 90% specificity, a 61% positive predictive value (PPV), a 90% negative predictive value, and an area under the receiver operating characteristic curve value of 0.91; these values were higher than those obtained from assays for IgA against DGP or IgG against TTG plus DGP. Not including the test for DGP antibody caused only 0.18% of celiac disease cases to be missed. Level of TTG IgA 7-fold the upper limit of normal (ULN) identified patients with celiac disease with a 96% PPV and 100% specificity. Using CART analysis, we found a level of TTG IgA 3.2-fold the ULN and higher to most accurately identify patients with celiac disease (PPV, 89%). Multivariable CART analysis showed that a level of TTG IgA 2.5-fold the ULN and higher was sufficient to identify celiac disease in patients with type 1 diabetes (PPV, 88%). Serum level of IgA against TTG in patients with versus those without trisomy 21 did not affect diagnosis predictability in CART analysis.


In a population-based study, we found that serum level of IgA against TTG can identify patients with celiac disease with PPVs of about 90%. Predictive values increase greatly when levels are markedly above the ULN or when the assay is used in combination with other variables. Measurement of IgG against TTG or DGP does not increase the accuracy of detection of celiac disease based against TTG IgA levels. There is a low risk of false-positive results from serologic analysis in patients with type I diabetes or persistent increases in antibody against TTG on repeat testing.

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