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Not yet recruiting NCT06275997

GAIN Project: Gastric Cancer and Artificial Intelligence

No phase Interventional Gastric 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
The protocol lists: Integration of Artificial Intelligence (AI) assistance to screening gastroscopy.
Who it may be relevant to
Registry conditions: Gastric Cancer. Basic parameters: from 60 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 →
Official title

Gastric Cancer and Artificial Intelligence: a National-level Project

Overview

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).

Interventions

  • Device Integration of Artificial Intelligence (AI) assistance to screening gastroscopy
    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

Primary outcome measures

  • Miss rate reduction [Time frame: 2025: 12 months enrollment]
Secondary outcome measures (2)
  • Change number of Detections [Time frame: 1 day procedure and follow up for 2 years]
  • patient satisfaction [Time frame: 2025: during the 12 months enrollment]

Eligibility criteria

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.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Prevention

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT06275997 · GAIN

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗