GAIN Project: Gastric Cancer and Artificial Intelligence

Our GAIN project comprises four core work packages (WPs): WP1. Nation-level randomized controlled trial; WP2. Development of an innovative AI tool; WP3. Novel microsimulation modelling; WP4. Patient inclusion.

The nation-level multi-center tandem randomized controlled trial (WP1) will contribute to a better understanding of how the real-time AI algorithm can reduce miss rate of early gastric cancer and dysplasia during gastroscopy. Moreover, the innovation project will contribute to development of a novel AI tool (WP2) that can stratify the risk of gastric cancer by identifying in vivo precancerous conditions. Furthermore, a microsimulation modelling will allow us to predict how the use of AI can prevent gastric cancer and affect cost and patients' burdens. The assessment of the balance between benefits and harms is quite crucial especially for this type of medical device because the value of innovative tools is sometimes overestimated due to stakeholders' enthusiasm (WP3). Finally, we will take care of patients' perspective throughout the study project by including patient organization in both WP1, 2, and 3 (WP4).

Not Yet Recruiting

Trial opening soon.

Get Notified

Key information

Conditions

Gastric Cancer Digestive System Diseases Digestive System Neoplasms Gastrointestinal Diseases Gastrointestinal Neoplasms Neoplasms Neoplasms by Site Stomach Diseases Stomach Neoplasms

Age range

60 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

All >60 years-old patients undergoing upper-gastrointestinal (GI) endoscopy for selected indications in Italian areas at high-risk of gastric cancer (Lombardia, Emilia Romagna, Veneto, Friuli-Venezia Giulia).

Exclusion criteria

contraindications to upper-GI endoscopy.
contraindications to biopsy.
active upper-GI bleeding or urgent upper-GI endoscopy.
patients with previous upper-GI surgery involving the stomach.
patients who were not able or refused to give informed written consent.

Treatment and study plan

Integration of Artificial Intelligence (AI) assistance to screening gastroscopy

Device

Two novel deep learning systems, namely one for endoscopy and one for pathology, will be trained and validated for the diagnosis of gastric atrophy and metaplasia, including extension and severity. Both of the algorithms will be validated against the cases not used for the training phases. Approximately, the partition will be 5 to 1.

The benefit and harm of AI-assistance for early diagnosis of gastric cancer will be simulated by developing a Markov model on the natural history of gastric cancer from dysplasia to early and advanced cancer, as well as by the impact of a GS on its natural history. This will also simulate the potential effect of lead- and length-time bias. These data will be incorporated in the simulation model in order to include them in the decision-making process on whether AI-assistance for gastric cancer detection should be or not recommended to health systems.

Primary outcomes

Miss rate reduction

Time frame: 2025: 12 months enrollment

change of the miss rate of early gastric cancer and dysplastic lesions at upper-endoscopy when using AI-assistance (tandem).

Secondary outcomes

Change number of Detections

Time frame: 1 day procedure and follow up for 2 years

Change in the detection of early gastric cancer and dysplastic lesions at upper-endoscopy when using AI-assistance (parallel).
patient satisfaction

Time frame: 2025: during the 12 months enrollment

Assessment of patient acceptability, satisfaction and tolerance, assessed by questionnaire, towards AI technology for both the detection and the characterization of gastric lesions.

Sponsors and collaborators

Lead sponsor

Istituto Clinico Humanitas

Other

Registry information

Official study title

Gastric Cancer and Artificial Intelligence: a National-level Project

Acronym: GAIN

Important dates

Study start: 2024
Primary completion: 2026
Study completion: 2028
First posted: Feb 23, 2024
Registry last updated: Jun 4, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Not Yet Recruiting