Urine Metabolites in the Diagnosis of Disease

Condition(s) studied

Study summary

The goal of this observational study is to validate a non-invasive, urine-based diagnostic technology for the detection and differentiation of various gastrointestinal (GI) diseases.

This research study intends to enroll participants across a range of demographics and GI disease states including colorectal cancer, small intestinal bacterial overgrowth (SIBO), Crohn\'s disease, and Celiac disease, collect urine samples and clinical data, and use artificial intelligence and machine learning to build disease-specific models which can identify and differentiate a participants' specific GI disease.

The main questions it aims to answer are:

1. Does the platform identify a disease signal within each disease cohort, compared to normal controls?
2. How well does the test perform (e.g. sensitivity and specificity/false-positive rate)?

Eligibility

Primary outcome measure(s)

• Disease signal detection — From date of enrollment to the end of sample analysis, up to 100 weeks
  Disease signal detection quantification within each disease cohort, compared to normal controls.
• Test performance measures — From date of enrollment to the end of sample analysis, up to 100 weeks
  Sensitivity and specificity/false-positive rate

Trial sites (4)

Other trials for the same condition