Observations On A Large Sample Set Using Serologic Markers To Predict Inflammatory Bowel Disease, Ulcerative Colitis (Uc), And Crohn'S (Cd)

Purpose: Over the past 10 years serological tests have been developed to predict IBD and multiple serologic markers utilized in this process contribute to the complexity of the analysis. Prometheus has developed an algorithmic method to aid in resolving this complexity and to predict IBD. This observational study presents data on the use of this algorithm in a large cohort of samples. Methods: Over an extended period of time 47,017 samples were received at Prometheus for IBD testing with unkown clinical diagnosis. All samples were tested for several serological markers including ANCA, ASCA, Anti-OmpC, and Anti CBir-1. Results: The Prometheus smart diagnostic algorithm predicted CD in 34% (16,058), UC in 11% (4,973), and non-IBD in 55% (25,986) of the samples received. In order to investigate the contribution of individual markers to the prediction, cut off analysis was performed for each of the 3 categories of predictions. In the cut off analysis, a marker was positive if its value was 2 standard deviations above a mean value calculated for non-disease controls. For CD a cut-off analysis was done using the following 4 markers: ASCA, Anti-CBir-1, Anti-OmpC and ANCA. Of the 16,058 CD predictions 86%, 28%, 14%, and 6% were positive for one, two, three, or 4 markers respectively. In this analysis the predominant single marker was Anti-Cbir-1 followed by ASCA. In addition, 14% of the CD predicted samples had all makers below cut-offs. For UC a cut-off analysis was done using the same markers as were used for the CD analysis. Of the 4,973 UC predictions 92%, 26%, 8%, and 1% were positive for one, two, three, or 4 markers respectively. In this Analysis the most predominant marker was ANCA followed by Anti-OmpC. In addition, 8% of the UC predicted samples had all makers below cut-offs. For the non IBD category of prediction, 64% of all markers were below cut off and 31% of the predictions have one marker above cut off and in this analysis the predominant single marker was Anti-CBir-1 followed by Anti-OmpC. Conclusion: These data are consistent with published frequency of the four previously identified serologic markers in IBD and indicate that IBD is a very heterogeneous and complex disease. The number of markers required to predict disease and the complexity of marker patterns is best served by a sophisticated algorithmic approach. Results also indicate that a significant number of patients predicted to have either CD or UC have serology markers below the normal cut-offs.