The Research of Constructing a Risk Assessment Model for Gastric Cancer Based on Machine Learning

NCT ID: NCT04957407

Last Updated: 2021-07-12

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 5000 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2019-01-01
• Study Completion Date: 2022-12-31

Brief Summary

Based on the gastric cancer database established earlier, this project explored the PG standard suitable for Chinese people, and further explored the establishment of machine learning model to stratify gastric cancer risk in the population, guide the frequency of gastroscopy screening, and extract important gastric cancer risk factors from it.Establish electronic health records of gastric organs, track the development and outcome of gastric diseases through deep learning method, in order to predict the development and outcome of gastric diseases;Then, the simulation hypothesis deductive method is used to compare the outcomes that may be caused by different lifestyles with the help of deep learning model, so as to guide patients to develop a better lifestyle and explore the establishment of health management paths for gastric cancer patients and high-risk groups in China.

Conditions

Gastric Cancer; Precancerous Lesion; Mechine Learning

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

non-atrophic gastritis

OLGA-0 group；OLGA (Operative Link on Gastritis Assessment)

No interventions assigned to this group

mild-moderate atrophic gastritis

OLGA I-II group；OLGA (Operative Link on Gastritis Assessment)

No interventions assigned to this group

severe atrophic gastritis

OLGA III-IV group；OLGA (Operative Link on Gastritis Assessment)

pepsinogen

Intervention Type: OTHER

diagnostic value of pepsinogen for severe atrophy and gastric cancer

gastric cancer

gastric cancer

pepsinogen

Intervention Type: OTHER

diagnostic value of pepsinogen for severe atrophy and gastric cancer

Interventions

pepsinogen

diagnostic value of pepsinogen for severe atrophy and gastric cancer

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• 1） intention to undergo gastroscopy during health checkup examination; and 2) 25-75 years of age

Exclusion Criteria

• 1) a history of gastric ulcer, gastric polyp, or GC; 2) a history of gastrectomy; 3) treatment with a proton pump inhibitor in the last month; 4) contraindications to gastroscopy; 5) a history of Hp eradication; 6) a history of abdominal pain, abdominal distention, belching, acid reflux, nausea and other digestive tract symptoms within 1 month or 67) incomplete data.

• Minimum Eligible Age: 25 Years
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Second Affiliated Hospital, School of Medicine, Zhejiang University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Yuling Tong, Dr.

Role: PRINCIPAL_INVESTIGATOR

2nd affiliated hospital of Zhejiang University, school of medicine

Locations

Zhejiang Provincial Hospital of Traditional Chinese Medicine

Hangzhou, , China

Site Status: RECRUITING

Ningbo cadres health center

Ningbo, , China

Site Status: RECRUITING

Countries

China

Central Contacts

Yuling Tong, Dr.

Role: CONTACT

tongyl0313@zju.edu.cn

1375821220

Yi Zhao, Master

Role: CONTACT

Facility Contacts

Xuan Huang

Role: primary

Tong Huang

Role: primary

Other Identifiers

71804161

Identifier Type: -

Identifier Source: org_study_id