AI-Based Risk Prediction Model for Upper Digestive Tract Cancer
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Gastric Cancer (GC), Premalignant Lesion, Gastric Intestinal Metaplasia, Atrophic Gastritis. Basic parameters: from 40 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Development of Artificial Intelligence Risk Prediction Model for Upper Digestive Tract Cancer Using High Resolution Endoscopic Image, Digital Pathology, Genetics, and Oro-gastro-intestinal Microbiota.
Overview
Upper digestive tract cancers are often preceded by pre-malignant lesions, but there is limited evidence regarding optimal risk prediction models and screening strategies for disease progression and cancer development. This prospective multicenter cohort study aims to establish a longitudinal database integrating clinical information, endoscopic findings, pathology, genetics, epigenetics, and gastrointestinal microbiota data from subjects undergoing upper digestive tract endoscopy. The study will develop explainable artificial intelligence (AI)-based risk prediction models to identify factors associated with disease progression, treatment response, and cancer development. Participants will be followed longitudinally to evaluate changes in lesion severity and clinical outcomes.
Detailed description
Objectives:
There is no solid evidence about the risk prediction model and screening duration for upper digestive tract pre-malignant lesions and its progression. There is also no longitudinal study combining multi-omic approach, endoscopic and pathologic images and the association with disease development. Hence we design a prospective cohort targeting upper digestive tract disease progression and cancer development, with standardized clinical data collection, quality control and explainable AI (artificial intellegence) model for better reliability of risk prediction model.
Aims:
We aim to develop risk prediction model for the progression of upper digestive tract disease and cancer development.
Methods:
The study is disigned as a multi-center prospective cohort, targeting subjects undergoing upper digestive tract endoscopy. The development of AI risk prediction models will combine endoscopic pre-malignant lesion, pathology, genetics, epigenetics, oro-gastro-intestinal microbiota, and follow-up longitudinally with change in lesion severity, medication response, cancer development.
Outcome measurement:
Primary endpoints: upper digestive tract cancer development. Secondary endpoints: progression in pre-malignant lesions, recurrent colon polyps, other cancer developement, metabolic and cardiovascular disease, response to medication in gastro-esophageal reflux and dyspepsia population.
Primary outcome measures
- Number of participants with upper digestive tract cancer confirmed by histopathological examination [Time frame: "From enrollment to the end of follow-up at 10 years"]
Secondary outcome measures (5)
- Number of participants with progression of gastric premalignant lesions assessed by OLGA, OLGIM, and EGGIM staging systems [Time frame: From enrollment to the end of follow-up at 10 years]
- Recurrent colon polyps [Time frame: From enrollment to the end of follow-up at 10 years]
- Number of participants with non-upper digestive tract malignancies confirmed by histopathological examination [Time frame: From enrollment to the end of follow-up at 10 years]
- Number of participants with newly diagnosed metabolic and cardiovascular diseases [Time frame: From enrollment to the end of follow-up at 10 years]
- Number of participants with symptom or endoscopic improvement after medication treatment in gastroesophageal reflux disease and dyspepsia populations [Time frame: From enrollment to the end of follow-up at 10 years]
Eligibility criteria
Inclusion criteria
- Patients undergoing upper gastrointestinal endoscopy.
- Patients with at least one of the following conditions or indications:
- Previous or current Helicobacter pylori infection (confirmed by serology, histopathology, urea breath test, rapid urease test, or stool antigen test);
- Dyspeptic symptoms;
- Gastroesophageal reflux disease;
- History of oral, oropharyngeal, or hypopharyngeal squamous cell carcinoma;
- Barrett's esophagus;
- Gastric premalignant lesions (intestinal metaplasia or atrophic gastritis);
- Gastric subepithelial lesions.
Exclusion criteria
\-
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Cohort
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07605312 · 202105028RINC