Personalized Approach to Celiac Disease Diagnosis
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 15,500
- 主要终点
- Aim 2 Interview Transcript Coding
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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
排除标准
- •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
- •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)
- •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)
研究组 & 干预措施
Aim 1 Retrospective Cohort
11300 patients evaluated for celiac disease from 1/1/2005-12/31/2021 from various sites, as well as 4000 internal patients evaluated from 1/1/2022-September 2025 will be used to validate the AI model. All 15300 patients are from a previously IRB approved study that had the goal of using for AI model validation.
Aim 2 Interview Cohort
30 patients with celiac disease will be recruited to participate in interviews regarding preferences in the diagnostic approach to celiac disease. Approximately 20 physicians (primary care, gastroenterology, and subspeciality physicians from Cleveland Clinic, identified based on their past one-year total number of patients diagnosed with celiac disease, selecting those in the top quartile of each specialty) will be interviewed regarding typical celiac diagnostic approach, concerns about use of a prediction model, etc. Finally, up to 5 physician-leaders (in Gastroenterology, including the Department Chair, General Gastroenterology Section Head, and members of the clinical practice committee) will be interviewed on perspectives on changing the clinical workflow, comfort with use of clinical prediction models for diagnosis, including liability, etc
Aim 3 Survey Cohort
100 patients will be asked to complete online surveys and consent to have their data input in the AI model.
结局指标
主要结局
Aim 2 Interview Transcript Coding
时间窗: 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
时间窗: 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.
Aim 1 Prediction Model
时间窗: 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.
次要结局
未报告次要终点
研究者
Claire Jansson-Knodell
Assistant Professor of Medicine
The Cleveland Clinic