A Novel Algorithm for the Diagnosis of Celiac Disease and a Comprehensive Review of Celiac Disease Diagnostics

There is an urgent clinical need for a better laboratory celiac disease diagnosis with both less false positive results and minimal underdetection. The aim of the present study was to evaluate the performance and diagnostic accuracy of different assays in an outpatient population setting for the diagnosis for celiac disease (CD) in order to design an optimal algorithm. We used 15 different ELISA assays to assess 47 blood samples of newly diagnosed children (positive biopsy results) and 52 samples from age- and sex-matched children with negative biopsy results for CD. Scoring criteria were established for grading the assays performance and characteristics. The combined gliadin and tTG assays exhibited the best sensitivity (100%). The addition of other assays to the CeliCheck neo-epitopes assay improved specificity so that the final algorithm had 100% sensitivity, 96.2% specificity, and 98.1% accuracy. The clinical demand for both maximal sensitivity and maximal specificity cannot be achieved with a single test. Using a combination of a sensitive assay together with specific assays improved celiac disease detection rates, with an acceptable number of false positive results. This model, however, needs to be confirmed prospectively in both children and adults.