Clinical trial · Observational
AI-Based Phenome Data Analysis for Predicting the Onset of Major Diseases
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 26, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260926-000001
Summary
Brief summary (as posted)
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 65 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
Conditions (5)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Breast Neoplasms | Breast Neoplasm | ONTOLOGY_EXACT | 0.98 |
| Cardiovascular Diseases | — | UNRESOLVED | — |
| Diabetes Mellitus Type 2 | — | UNRESOLVED | — |
| Low Back Pain | — | UNRESOLVED | — |
| Osteoarthritis | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (2)
- label
- Disease Group
- description
- Adults aged 30 to 65 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.
- label
- Healthy Control Group
- description
- Adults aged 30 to 65 years without five major diseases.
Primary outcomes (1)
- measure
- Number of Participants With Incident Target Disease or Condition Identified Up to 10 Years After the Index Date
- timeFrame
- Up to 10 years after the index date
- description
- 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.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 30 Years
- Maximum age
- 65 Years
Show eligibility criteria text
Inclusion Criteria: 1. Adults aged 30 to 65 years. 2. 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. 3. Healthy control group: Participants with no prior diagnosis of type 2 diabetes mellitus, breast cancer, cardiovascular disease, osteoarthritis, or low back pain. 4. 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. 5. Ability to understand the study procedures and provision of written informed consent prior to participation. Exclusion Criteria: 1. Participants with incomplete or insufficient clinical or health screening data. 2. Participants considered inappropriate for study participation by the investigator.
References
Publications (0)
Data not yet available