AI-Based Risk Prediction Model for Upper Digestive Tract Cancer
Ориентир для пациента и семьи
Простыми словами
Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.
- Что изучают
- Это наблюдательное исследование: исследуемое лечение участникам по протоколу не назначают.
- Кому может быть актуально
- Состояния в реестре: Gastric Cancer (GC), Premalignant Lesion, Gastric Intestinal Metaplasia, Atrophic Gastritis. Базовые параметры: от 40 лет · Все.
- Что важно проверить
- Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
- Где проводится
- Список центров уточняется — проверьте первичный протокол.
- Следующий шаг
- Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
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Официальное название
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.
Обзор
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.
Подробное описание
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.
Первичные конечные точки
- Number of participants with upper digestive tract cancer confirmed by histopathological examination [Срок оценки: "From enrollment to the end of follow-up at 10 years"]
Вторичные конечные точки (5)
- Number of participants with progression of gastric premalignant lesions assessed by OLGA, OLGIM, and EGGIM staging systems [Срок оценки: From enrollment to the end of follow-up at 10 years]
- Recurrent colon polyps [Срок оценки: From enrollment to the end of follow-up at 10 years]
- Number of participants with non-upper digestive tract malignancies confirmed by histopathological examination [Срок оценки: From enrollment to the end of follow-up at 10 years]
- Number of participants with newly diagnosed metabolic and cardiovascular diseases [Срок оценки: 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 [Срок оценки: From enrollment to the end of follow-up at 10 years]
Критерии участия
Критерии включения
- 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.
Критерии исключения
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Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.
Здоровые добровольцы: Да
Дизайн исследования
- Модель наблюдения
- Когортное
Центры проведения
Список центров уточняется — проверьте первичный протокол.
Идентификаторы
NCT: NCT07605312 · 202105028RINC