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NCT Number: NCT04840056

Prediction of Gastric Cancer in Intestinal Metaplasia and Atrophic Gastritis

The primary objectives of this study are:

* To identify clinical or histological factors associated with gastric cancer development in patients with IM and AG * To establish a machine learning algorithm for prediction of future gastric cancer risks and individual risk stratification in patient with IM and AG

Recruiting

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Key information

Conditions

Gastric Cancer Atrophic Gastritis Digestive System Diseases Digestive System Neoplasms Gastritis Gastritis, Atrophic Gastroenteritis Gastrointestinal Diseases Gastrointestinal Neoplasms Intestinal Metaplasia Neoplasms Neoplasms by Site Stomach Diseases Stomach Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Prince of Wales Hospital

Shatin, New Territories, Hong Kong

Location status: Recruiting

About this study

This is a two-part retrospective study including a clinical data part and a pathology part. A training cohort will be developed from approximately 70% of included cases. It will be followed by a validation cohort with the remaining cases.

Clinical data will be collected retrospectively using the Clinical Data Analysis and Reporting System (CDARS) and Clinical management System (CMS). A cluster-wide cohort (New Territories East Cluster, NTEC) consisting of patients with history of histologically-proven gastric IM and AG will be identified and included for subsequent analysis. The data collection period for the retrospective data will be 2000-2020.

Histology slides will be retrieved retrospectively when available (within NTEC). Whole slide imaging technique will be utilized for the development of training and validation cohorts with machine learning algorithms in the pathology part.

Who can participate

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

Inclusion criteria

  • Adults >= 18 years of age
  • Histologically proven atrophic gastritis or intestinal metaplasia (at antrum and/or body and/or angular of stomach)

Exclusion criteria

  • none

Treatment and study plan

Primary outcomes

  1. Gastric cancer and gastric dysplasia

    Time frame: 20 years

    The primary endpoint is the incidence of gastric cancer (intestinal-type) and gastric dysplasia (low grade and high grade dysplasia).

Secondary outcomes

  1. Overall accuracy of machine learning model

    Time frame: 20 years

    Overall accuracy of machine learning models will be evaluated

  2. Sensitivity of machine learning model

    Time frame: 20 years

    Sensitivity of machine learning model will be evaluated

  3. Specificity of machine learning model

    Time frame: 20 years

    Specificity of machine learning model will be evaluated

  4. Positive predictive value of machine learning model

    Time frame: 20 years

    Positive predictive value of machine learning model will be evaluated

  5. Negative predictive value of machine learning model

    Time frame: 20 years

    Negative predictive value of machine learning model will be evaluated

  6. Area under the receiver operating characteristic curve of machine learning model

    Time frame: 20 years

    Area under the receiver operating characteristic curve of machine learning model will be evaluated

Study contacts

Contact information is provided by the study sponsor or research team.

Felix Sia

CONTACT

[email protected]

+85226370428

Thomas Lam

CONTACT

[email protected]

+85226370428

Sponsors and collaborators

Lead sponsor

Chinese University of Hong Kong

Other

Registry information

Official study title

Prediction of Gastric Cancer in Intestinal Metaplasia and Atrophic Gastritis - Application of Artificial Intelligence in Histology and Clinical Data

Acronym: GIMA

Important dates

Study start
2021
Primary completion
2025
Study completion
2025
First posted
Apr 9, 2021
Registry last updated
Aug 29, 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.

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