Sub-healthyNCT07375303
Data Mining of Population Health-sub-health-disease Based on Dynamic System Theory
An observational study of Sub-healthy, run by Beijing Friendship Hospital at 1 site in China.
Trial summary
This study aims to explore the dynamic evolution patterns of population health, sub-health, and disease states through dynamic system theory and big data mining methods, providing scientific evidence for personalized prevention and health management. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Sub-healthy
- Type of treatment
- Injection or infusion
- How many people
- 380,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2025to 31 Aug 2030
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Health Data Science Database of Beijing Friendship Hospital
Who may be able to join
- Participants must have completed at least two consecutive physical examinations at the Physical Examination Center of Beijing Friendship Hospital, Capital Medical University, between June 2007 and August 2025, with a minimum interval of 6 months between adjacent records.
- Data records should be relatively complete, with missing rates for key research variables (e.g., core biochemical indicators, demographic information, and essential questionnaire items) ≤30%.
- Participants must have no prior history of severe organic diseases prior to their first study inclusion (as documented in medical records, primarily including: malignant tumors (non-curable/end-stage), severe cardiac insufficiency (NYHA Class III-IV), end-stage renal disease (CKD Stage 5), decompensated cirrhosis, or significant functional impairment caused by sequelae of severe cerebrovascular disease).
Who cannot join
- Individuals with a severe lack of basic data (such as unique identification, key demographic information, and core indicators of detection) or who cannot be effectively anonymized.
Trial locations and contacts
1 site in 1 country.
China1 site
Beijing Friendship Hospital, Capital Medical University
Beijing, Beijing Municipality, 100050
About this study
This study aims to explore the dynamic evolution patterns of population health, sub-health, and disease states through dynamic system theory and big data mining methods, providing scientific evidence for personalized prevention and health management.
Read the detailed description
Specific objectives include: (1) Identifying individual health, sub-health, and disease states using unsupervised system modeling techniques, while investigating their mutual transformation pathways. (2) Identifying key indicators determining state transitions, clarifying their mechanisms and interactions. (3) Developing dynamic system models to simulate state transition trajectories under multivariate influences, predicting individual probabilities of progression from health to sub-health or disease. (4) Creating interpretable health prediction tools based on modeling results to support precision interventions. The ultimate goal is to establish a scientifically validated yet implementable health state modeling system, offering quantifiable tools for early intervention and personalized health management to reduce chronic disease incidence and healthcare burdens.
- Conditions
- Sub-healthy
- Being tested
- No intervention will be applied.
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No intervention will be applied.Other
This is an observational study.
| Study group | Role | What they receive |
|---|---|---|
| Health Data Science Database of Beijing Friendship Hospital | 1. Participants must have completed at least two consecutive physical examinations at the Physical Examination Center of Beijing Friendship Hospital, Capital Medical University, between June 2007 and August 2025, with a minimum interval of 6 months between adjacent records.
2. Data records should be relatively complete, with missing rates for key research variables (e.g., core biochemical indicators, demographic information, and essential questionnaire items) ≤30%.
3. Participants must have no prior history of severe organic diseases prior to their first study inclusion (as documented in medical records, primarily including: malignant tumors (non-curable/end-stage), severe cardiac insufficiency (NYHA Class III-IV), end-stage renal disease (CKD Stage 5), decompensated cirrhosis, or significant functional impairment caused by sequelae of severe cerebrovascular disease). Receives: Other: No intervention will be applied. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Discriminative Accuracy for Next Diagnosis
Age- and Sex-stratified Area Under the Receiver Operating Characteristic Curve, AUC
Measured: Evaluate on an internal validation dataset. This dataset contains individual historical data up to January 1, 2018, based on which the model predicts the next diagnostic event that will occur immediately. Calculate AUC for diseases with over 1000 ICD-10
Long-term Predictive Accuracy
AUC stratified by age and gender, assessing the risk of disease occurrence within specific time intervals (1 year, 2 years,..., 10 years) after prediction. This indicator measures the decay of a model's predictive ability over time.
Measured: Evaluate the AUC values of disease occurrence in the 1st, 2nd, 3rd, 5th, and 10th year after prediction on the internal validation dataset.
Trajectory-level Predictive Accuracy
The proportion of correctly predicted disease events. In each simulated future year, match the generated disease events with the actual disease events that occur in individuals, and calculate the success rate (%) of the matching.
Measured: On the validation subset, evaluate the accuracy of disease event predictions for each year from the simulation starting point (60 years old) to the following 1 to 20 years.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Jan 2026
- Study start1 Sep 2025
- Primary completion31 Aug 2028 (estimated)
- Study completion31 Aug 2030 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Sub-healthyStudies of the same condition, open and under way.
- More trials run by Beijing Friendship HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 380,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Beijing Friendship Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Lv, Han, Beijing Friendship Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07375303
- Sponsor's protocol ID
- 202511
- Status last verified
- Jan 2026
- First submitted
- 9 Dec 2025
- Last updated
- 29 Jan 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 29 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Data Mining of Population Health-sub-health-disease Based on Dynamic System Theory
- ClinicalTrials.gov ID
- NCT07375303
- Acronym / sponsor ID
- 202511
- Conditions
- Sub-healthy
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 380,000 participants (estimated)
- Lead sponsor
- Beijing Friendship HospitalUniversity, hospital or other
- Study start
- 1 Sep 2025 (actual)
- Primary completion
- 31 Aug 2028 (estimated)
- Study completion
- 31 Aug 2030 (estimated)
- First posted
- 29 Jan 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to explore the dynamic evolution patterns of population health, sub-health, and disease states through dynamic system theory and big data mining methods, providing scientific evidence for personalized prevention and health management.
Detailed description
Specific objectives include: (1) Identifying individual health, sub-health, and disease states using unsupervised system modeling techniques, while investigating their mutual transformation pathways. (2) Identifying key indicators determining state transitions, clarifying their mechanisms and interactions. (3) Developing dynamic system models to simulate state transition trajectories under multivariate influences, predicting individual probabilities of progression from health to sub-health or disease. (4) Creating interpretable health prediction tools based on modeling results to support precision interventions. The ultimate goal is to establish a scientifically validated yet implementable health state modeling system, offering quantifiable tools for early intervention and personalized health management to reduce chronic disease incidence and healthcare burdens.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Health Data Science Database of Beijing Friendship Hospital | – | Other: No intervention will be applied.1. Participants must have completed at least two consecutive physical examinations at the Physical Examination Center of Beijing Friendship Hospital, Capital Medical University, between June 2007 and August 2025, with a minimum interval of 6 months between adjacent records. 2. Data records should be relatively complete, with missing rates for key research variables (e.g., core biochemical indicators, demographic information, and essential questionnaire items) ≤30%. 3. Participants must have no prior history of severe organic diseases prior to their first study inclusion (as documented in medical records, primarily including: malignant tumors (non-curable/end-stage), severe cardiac insufficiency (NYHA Class III-IV), end-stage renal disease (CKD Stage 5), decompensated cirrhosis, or significant functional impairment caused by sequelae of severe cerebrovascular disease). |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Health Data Science Database of Beijing Friendship Hospital
Key inclusion criteria (3 listed)
- Participants must have completed at least two consecutive physical examinations at the Physical Examination Center of Beijing Friendship Hospital, Capital Medical University, between June 2007 and August 2025, with a minimum interval of 6 months between adjacent records.
- Data records should be relatively complete, with missing rates for key research variables (e.g., core biochemical indicators, demographic information, and essential questionnaire items) ≤30%.
- Participants must have no prior history of severe organic diseases prior to their first study inclusion (as documented in medical records, primarily including: malignant tumors (non-curable/end-stage), severe cardiac insufficiency (NYHA Class III-IV), end-stage renal disease (CKD Stage 5), decompensated cirrhosis, or significant functional impairment caused by sequelae of severe cerebrovascular disease).
Key exclusion criteria (1 listed)
- Individuals with a severe lack of basic data (such as unique identification, key demographic information, and core indicators of detection) or who cannot be effectively anonymized.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| No intervention will be applied.This is an observational study. | Other | Health Data Science Database of Beijing Friendship Hospital |
Primary outcome
Discriminative Accuracy for Next Diagnosis
Time frame: Evaluate on an internal validation dataset. This dataset contains individual historical data up to January 1, 2018, based on which the model predicts the next diagnostic event that will occur immediately. Calculate AUC for diseases with over 1000 ICD-10
Age- and Sex-stratified Area Under the Receiver Operating Characteristic Curve, AUC
Long-term Predictive Accuracy
Time frame: Evaluate the AUC values of disease occurrence in the 1st, 2nd, 3rd, 5th, and 10th year after prediction on the internal validation dataset.
AUC stratified by age and gender, assessing the risk of disease occurrence within specific time intervals (1 year, 2 years,..., 10 years) after prediction. This indicator measures the decay of a model's predictive ability over time.
Trajectory-level Predictive Accuracy
Time frame: On the validation subset, evaluate the accuracy of disease event predictions for each year from the simulation starting point (60 years old) to the following 1 to 20 years.
The proportion of correctly predicted disease events. In each simulated future year, match the generated disease events with the actual disease events that occur in individuals, and calculate the success rate (%) of the matching.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Jan 2026.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sub-healthy, run by Beijing Friendship Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 29 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Discriminative Accuracy for Next Diagnosis (time frame: Evaluate on an internal validation dataset. This dataset contains individual historical data up to January 1, 2018, based on which the model predicts the next diagnostic event that will occur immediately. Calculate AUC for diseases with over 1000 ICD-10). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Jan 2026.