Personalized Approach to Celiac Disease Diagnosis

The goal of this observational study is to learn about an adult's chance of having celiac disease based on blood testing and symptoms. The main question it aims to answer is:

Can a blood test and symptom information separate patients into 3 groups of low, intermediate, and high risk for celiac disease?

Participants already being evaluated for celiac disease as part of regular medical care will answer online survey questions about symptoms and have laboratory data collected from charts.

The investigators hypothesize that a clinical prediction model integrating clinical data with TTG-IgA antibody levels can accurately identify patients with celiac disease offering a personalized approach. The investigators anticipate this prediction model would classify patients into 3 risk groups for celiac disease: 1) Low likelihood (no further testing required), 2) Intermediate likelihood (biopsy required for confirmation), and 3) High likelihood (biopsy can be avoided based on the model's accuracy) thereby reserving endoscopy and biopsies for cases of intermediate probability to improve diagnosis, reduce invasive testing, increase patient focus, and decrease costs.