Health TrialsbyHealthPanel

Prediction of Gastric Cancer in Intestinal Metaplasia and Atrophic Gastritis

ConditionsGastric CancerIntestinal MetaplasiaAtrophic Gastritis
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorChinese University of Hong Kong

About this trial

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

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Adults >= 18 years of age

Histologically proven atrophic gastritis or intestinal metaplasia (at antrum and/or body and/or angular of stomach)

Disqualifiers

None

Trial population

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.

Trial design

Design model

Cohort

Time perspective

Retrospective

Treatments tested in this trial

Not listed

Trial groups

1,300 Participants
are grouped into 2 trial groups
Group A: Intestinal Metaplasia
Group B: Atrophic gastritis

Trial outcomes

Primary outcomes

1

Gastric cancer and gastric dysplasia

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

Time frame
20 years

Secondary outcomes

1

Overall accuracy of machine learning model

Overall accuracy of machine learning models will be evaluated

Time frame
20 years
2

Sensitivity of machine learning model

Sensitivity of machine learning model will be evaluated

Time frame
20 years
3

Specificity of machine learning model

Specificity of machine learning model will be evaluated

Time frame
20 years
4

Positive predictive value of machine learning model

Positive predictive value of machine learning model will be evaluated

Time frame
20 years

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Chinese University of Hong Kong

Lead sponsor

Source ClinicalTrials.gov
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