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NCT Number: NCT07701655

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.

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Key information

Conditions

Celiac Disease Digestive System Diseases Gastrointestinal Diseases Intestinal Diseases Malabsorption Syndromes Metabolic Diseases Nutritional and Metabolic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

About this study

The specific aims of this study are to: 1) develop and validate a clinical prediction model for celiac disease probability (external validation will be performed by site and time), 2) evaluate the implementation potential of the model, and 3) pilot the model and determine its impact on patient experience.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

For Aim 1:

Inclusion criteria

Patients ≥18 who underwent duodenal biopsy during upper endoscopy and had a TTG-IgA antibody test 3 months before or 1 month after biopsy

Exclusion criteria

Patients with a prior diagnosis of celiac disease undergoing biopsy and TTG-IgA antibody testing for follow-up care
Children and vulnerable populations (e.g. pregnant women or prisoners)
Patients with IgA deficiency
Patients already following a gluten-free diet

For Aim 2:

Inclusion criteria

Physicians (primary care or subspeciality) who test or evaluate patients for celiac disease
Patients already diagnosed with celiac disease or undergoing evaluation for celiac disease

Exclusion criteria

Children and vulnerable populations (e.g. pregnant women or prisoners)

For Aim 3:

Inclusion criteria

Patients ≥18 with a standard-of-care celiac disease evaluation (both TTG-IgA antibody and upper endoscopy with duodenal biopsy)
Willing to participate and able to provide informed consent

Exclusion criteria

Children and vulnerable populations (e.g. pregnant women or prisoners)

Treatment and study plan

Primary outcomes

Aim 1 Prediction Model

Time frame: 1 year

The primary outcome being predicted is biopsy-confirmed celiac disease, defined as villous atrophy on duodenal histopathology. A prediction model will be built and after final model construction, the investigators will report its performance using five established measures: sensitivity, specificity, positive predictive value, negative predictive value, and F-measure. A calibration plot will be produced to illustrate if the model's predicted probabilities of an outcome reflect the true outcome probability. The investigators will use the SHapley Additive exPlanation (SHAP) method to provide a list of all model features ranked according to relative importance.
Aim 2 Interview Transcript Coding

Time frame: Years 2-3

Interview transcripts will be uploaded into NVivo software, a qualitative data analysis tool that facilitates coding of source data and identification of similarities in coded concepts indicative of themes. A research assistant and the PI will independently inductively code interviews in NVivo. Data-driven codes will be combined with a priori codes corresponding to the PRISM domains to develop the study codebook and summarize themes. We will map these codes to the PRISM framework to understand how the intervention, recipients, implementation structure, and external environment interact to support implementation of a prediction model for celiac disease diagnosis.
Aim 3 Model Performance and Patient Preferences

Time frame: Years 4-5

For aim 3, the primary outcome of interest will be model accuracy reported as AUC, AUPRC, sensitivity, and specificity. We will describe patient-reported preferences for communication and display of the prediction model, as well as ranking of decisional attributes (e.g. discomfort, certainty in results). Best practices for survey reporting will be used.

Study contacts

Contact information is provided by the study sponsor or research team.

Claire Jansson-Knodell, MD

CONTACT

[email protected]

2164446354

Sponsors and collaborators

Lead sponsor

The Cleveland Clinic

Other

Collaborators

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

Registry information

Acronym: PACkeD

Important dates

Study start: 2026
Primary completion: 2030
Study completion: 2031
First posted: Jul 14, 2026
Registry last updated: Jul 20, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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