AI-Based Phenome Data Analysis for Predicting the Onset of Major Diseases

NCT07595718 | Recruiting

• 1 other identifier: 2026-0205
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to develop and validate an artificial intelligence (AI)-based predictive model to estimate the risk of incident onset of five major diseases or conditions: cardiovascular disease, type 2 diabetes mellitus, breast cancer, low back pain, and osteoarthritis, in adults aged 30 to 60 years. For each participant, an index date will be defined as the date of a prior health screening or another protocol-defined baseline clinical date. Incident disease status for each target disease or condition will be ascertained by retrospective review of electronic medical records for up to 10 years after the index date. The study integrates retrospective clinical, health screening, laboratory, imaging, and electronic medical record data with prospectively collected biospecimen, proteomic, genomic, questionnaire, lifestyle, and digital health data. Prospective study procedures will be completed over approximately 1 week, with up to 2 additional weeks if needed. By combining multimodal data, this study seeks to improve disease risk prediction and to identify clinical and biological factors associated with disease onset, ultimately supporting personalized risk stratification and preventive healthcare strategies.

Conditions

Diabetes Mellitus Type 2; Breast Neoplasms; Low Back Pain; Osteoarthritis; Cardiovascular Diseases

Outcome Measures

Primary Outcomes (1)

• Number of Participants With Incident Target Disease or Condition Identified Up to 10 Years After the Index Date

  Incident target disease or condition will be assessed for five prespecified target diseases or conditions: cardiovascular disease, type 2 diabetes mellitus, breast cancer, low back pain, and osteoarthritis. For each target disease or condition, incident occurrence will be defined as a new diagnosis recorded in electronic medical records after the index date among participants without that target disease or condition at the index date. Results will be summarized separately for each target disease or condition as the number and percentage of participants with incident disease or condition.

  Up to 10 years after the index date

Secondary Outcomes (5)

• Discriminative performance of the artificial intelligence model in distinguishing between disease and control groups using baseline data from health screenings and clinical records (AUROC, PR-AUC)

  Through study completion, approximately 9 months

• Diagnostic Performance of the Artificial Intelligence Model for Predicting Incident Target Diseases or Conditions

  Through study completion, approximately 9 months

• Brier Score of the Artificial Intelligence Model for Predicting Incident Target Diseases or Conditions

  Through study completion, approximately 9 months

• Calibration Slope of the Artificial Intelligence Model for Predicting Incident Target Diseases or Conditions

  Through study completion, approximately 9 months

• Calibration Intercept of the Artificial Intelligence Model for Predicting Incident Target Diseases or Conditions

  Through study completion, approximately 9 months

Study Arms (2)

Disease Group

Adults aged 30 to 60 years with one or more of the five major diseases. Five major diseases are Cardiovascular Diseases, Diabetes Mellitus, Type 2, Breast Neoplasms, Low Back Pain and Osteoarthritis.

Healthy Control Group

Adults aged 30 to 60 years without five major diseases.

Eligibility Criteria

• Age: 30 Years - 60 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

This study will involve two distinct groups of participants: a disease group and a healthy control group. 1. Disease Group: The disease group will consist of adults aged 30 to 60 years who have been diagnosed with at least one of the following conditions: Type 2 diabetes mellitus Breast cancer Cardiovascular disease Osteoarthritis Low back pain These participants will undergo questionnaires, digital assessments, physical examinations, and blood tests as part of the study. 2. Healthy Control Group: The healthy control group will consist of adults aged 30 to 60 years with no prior diagnosis of any of the conditions listed above (type 2 diabetes mellitus, breast cancer, cardiovascular disease, osteoarthritis, or low back pain). This group will also undergo similar assessments including questionnaires, physical examinations, and blood tests, but they will not have the aforementioned conditions.

You may qualify if:

• Adults aged 30 to 60 years.
• Disease group: Participants with a confirmed diagnosis of at least one of the following conditions: type 2 diabetes mellitus, breast cancer, cardiovascular disease, osteoarthritis, or low back pain.
• Healthy control group: Participants with no prior diagnosis of type 2 diabetes mellitus, breast cancer, cardiovascular disease, osteoarthritis, or low back pain.
• No history or current diagnosis of major medical conditions that may affect study outcomes, including but not limited to chronic kidney disease or liver cirrhosis.
• Ability to understand the study procedures and provision of written informed consent prior to participation.

You may not qualify if:

• Participants with incomplete or insufficient clinical or health screening data.
• Participants considered inappropriate for study participation by the investigator.

Sponsors & Collaborators

• Jae Yong Jeon, MD: lead

Study Sites (1)

Seoul Asan Medical Center

Seoul, Seoul Special City, 05505, South Korea

RECRUITING

Biospecimen

Retention: SAMPLES WITH DNA

Participants will undergo a total blood draw of approximately 15 mL, which will include routine laboratory testing as well as proteomic and genomic analyses.

MeSH Terms

Conditions

Diabetes Mellitus, Type 2; Breast Neoplasms; Low Back Pain; Osteoarthritis; Cardiovascular Diseases

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases; Back Pain; Pain; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Arthritis; Joint Diseases; Musculoskeletal Diseases; Rheumatic Diseases

Central Study Contacts

Jaeyong Jeon

CONTACT

+82-2-3010-3791; jyjeon71@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Week
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: April 18, 2026
• First Posted: May 19, 2026
• Study Start: April 2, 2026
• Primary Completion (Estimated): October 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: May 19, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

KR (1)