NCT05762991

Brief Summary

The aim of this diagnostic accuracy study is to evaluate the application of artificial intelligence on the diagnosis of Helicobacter pylori infection and premalignant gastric lesions based on upper endoscopic images. We use techniques of artificial intelligence to analyze the correlation between endoscopic images and urea breath test results/histopathological results.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
2,000

participants targeted

Target at P75+ for all trials

Timeline
8mo left

Started Dec 2021

Longer than P75 for all trials

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress87%
Dec 2021Dec 2026

Study Start

First participant enrolled

December 24, 2021

Completed
1.2 years until next milestone

First Submitted

Initial submission to the registry

February 28, 2023

Completed
10 days until next milestone

First Posted

Study publicly available on registry

March 10, 2023

Completed
3.8 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2026

Expected
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2026

Last Updated

June 22, 2025

Status Verified

June 1, 2025

Enrollment Period

5 years

First QC Date

February 28, 2023

Last Update Submit

June 17, 2025

Conditions

Helicobacter Pylori InfectionPremalignant Lesion

Keywords

Helicobacter, Artificial Intelligence, Telemedicine

Outcome Measures

Primary Outcomes (1)

  • Sensitivity to detect premalignant gastric lesions

    Outcomes include the atrophic gastritis, intestinal metaplasia, and Helicobacter pylori infection

    Up to 5 years

Secondary Outcomes (1)

  • Specificity to exclude premalignant gastric conditions

    Up to 5 years

Other Outcomes (2)

  • Areas under the ROC curves

    Up to 5 years

  • Gastric cancer incidence

    Up to 10 years

Study Arms (1)

Helicobacter pylori infection and premalignant gastric lesion

Application of artificial intelligence to analyze the correlation between endoscopic images and urea breath test results/histopathological results.

Eligibility Criteria

Age20 Years - 80 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

This study will invite patients who need to undergo urea breath test, upper gastrointestinal endoscopy and histology examination.

You may qualify if:

  • Age 20-80
  • Scheduled urea breath test and endoscopy

You may not qualify if:

  • \. History of gastric surgery

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Yi-Chia Lee

Taipei, 10015, Taiwan

RECRUITING

Study Officials

  • Tsung-Hsien Chiang, MD, PhD

    National Taiwan University Hospital

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Yi-Chia Lee, MD, PhD

CONTACT

886-2-23123456yichialee@ntu.edu.tw

Tsung-Hsien Chiang, MD,PhD

CONTACT

886-2-23123456thchiang@ntu.edu.tw

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
OTHER
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

February 28, 2023

First Posted

March 10, 2023

Study Start

December 24, 2021

Primary Completion (Estimated)

December 31, 2026

Study Completion (Estimated)

December 31, 2026

Last Updated

June 22, 2025

Record last verified: 2025-06

Locations

TW(1)