Clinical trial NCT06421324: Personalised Health Recommendations to the General Population Through an Integrated AI Guided
Official title: Interventional Study Focused on Providing Personalised Health Recommendations to the General Population Through an Integrated AI Guided App as a Strategy for Gastric Cancer Prevention (AIDA)
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Gastric Cancer
Cancer Prevention
Helicobacter Pylori Infection
Artificial Intelligence
Lead sponsor: Fundación para la Investigación del Hospital Clínico de Valencia
Sponsor class: OTHER
First posted: 2024-05-20
Enrollment: 450
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Intervention model description: In practice, for rare diseases we chose a sample size that will allow estimation of sensitivity of the risk score to a pre-specified precision. We have chosen the sample size assuming that the resulting precancer detection model will have a sensitivity of at least 85%, and so that the lower 95% confidence interval will exceed 76%, with 80% power. The R package MKmisc estimates sample size for a proportion based on the Binomial distribution rather than a Normal approximation. In this case, we have estimated a sample size of 141 GIM + cancer and 141 GIM controls (282 in total). With 5% of samples assumed to be failing to be analysed due to a variety of technical reasons, we would need \~300 samples in total. In addition, to train the system 150 gastric cancer cases will be recruited which will provide pathology samples images and endoscopy images that will be taken as part of the clinical practice.
Primary purpose: PREVENTION

Brief summary: This clinical study aims to be used to implement and validate the AIDA tool in two phases:

* Phase 1: Risk stratification and personalised recommendations \& Model development
* Phase 2: Mechanistic Model (Bioresource) development \& testing

Detailed description: The AIDA objective (project) is to develop and validate a multidisciplinary AI-powered assistant that helps clinicians diagnose precancerous inflammation, suggests personalised therapeutic strategies for medical treatment and follow-up, and makes personalised recommendations for monitoring patient health status, thus contributing to gastric cancer prevention. This prospective clinical study aims to implement and validate such tool.

Eligibility criteria: Inclusion Criteria:

* Subjects ≥ 18 years old with a diagnosis of GIM or previous or current H. pylori infection, to whom a gastroscopy is indicated within clinical care
* Availability of a signed informed consent form to participate in the study

Exclusion Criteria:

* Patients to whom an endoscopy is performed for the follow-up of another illness such as oesophageal varices and/or for therapy such as endoscopic dilation, feeding tube placement or endoscopic resection
* Subjects with a clinical diagnosis of gastric diseases other than GIM or GC
* Patients who have received antimicrobials during the four weeks prior to the endoscopy
* Patients who have received proton pump inhibitors and/or bismuth-based treatments at least two weeks prior to the endoscopy
* Subjects for whom clinical data are not available: H. pylori status, eradication treatment, sex, age, tobacco smoking, and first-degree family history of gastric cancer
* Subjects who lack the mental capacity to understand the nature and requirements of the study and who lack the ability to give informed consent

Primary outcomes:
measure: Risk of developing Gastric Cancer based on medical records
timeFrame: At the recruitment stage
measure: H. pylori Eradication Therapy Recommendation
timeFrame: From 30 days after the H.Pylori positive test result to one year after the first recommendation
measure: GIM risk score assessment using imaging modalities
timeFrame: At the recruitment stage
Secondary outcomes:
Other outcomes:
Locations:
city: Valencia
country: Spain
facility: Hospital Clínico Universitario de Valencia
Study officials:
affiliation: Fundación para la Investigación del Hospital Clínico de Valencia
name: Tania Fleitas, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References: