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RecruitingNCT07914907RABERUpdated Nov 4, 2026

GenAI-Assisted Rheumatoid Arthritis Bone Erosion Risk Assessment and DMARD Selection

An interventional study of GenAI-Assisted Clinical Decision Support for RABER Assessment and DMARD Selection in Rheumatoid Arthritis, sponsored by Guang'anmen Hospital of China Academy of Chinese Medical Sciences. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-11-04.

Sponsored by Guang'anmen Hospital of China Academy of Chinese Medical Sciences · Not applicable, Interventional, and Health services research

From the registry’s dates

  • Registered 7 months after the study started (first participant enrolled Mar 2026, registered Oct 2026).
  • Started Mar 2026; still recruiting 8 months later.
Updated Nov 4, 2026Newly registeredGo to Updates ↓
Phase
Not applicable
Study type
Interventional
Enrollment
100
Allocation
Not applicable
Ages
18 Years and older
Sex
All
01

Study summary

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive joint damage and bone erosion. Accurate assessment of RA bone erosion risk (RABER) and appropriate disease-modifying antirheumatic drug (DMARD) selection are critical to preventing irreversible disability.

Recent advances in generative artificial intelligence (GenAI), particularly large language models (LLMs), enable integration of heterogeneous clinical data and may improve clinical decision-making. However, there is limited real-world evidence (RWE) evaluating whether GenAI can meaningfully augment physician decision-making in routine care.

This prospective, single-arm, nonrandomized interventional study evaluates the feasibility and impact of GenAI-assisted clinical decision support on physician assessment of rheumatoid arthritis bone erosion risk and disease-modifying antirheumatic drug selection in routine inpatient care. Treating physicians document their initial risk assessments and treatment decisions before reviewing patient-specific GenAI reports and subsequently record their assessments and decisions after reviewing the reports. The study evaluates changes in physician clinical decision-making within a learning health system framework. Final treatment decisions remain under the responsibility of the treating physicians. The study does not evaluate long-term patient clinical outcomes.

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Conditions studied

  • Rheumatoid Arthritis

Keywords

  • RA bone erosion risk
  • GenAI prediction
  • LLMs
  • DMARD
  • real-world data
  • real-world evidence
  • learning health system unit
  • GenAI-assisted clinical decision support
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In context

Arthritis, Rheumatoid

2,971 studies on the registry are indexed under Arthritis, Rheumatoid; 399 are open to participants now.

This study's planned enrollment of 100 is close to the median of 94 across 2,034 interventional studies indexed under Arthritis, Rheumatoid.

Browse Arthritis, Rheumatoid studies →

Lead sponsor

Guang'anmen Hospital of China Academy of Chinese Medical Sciences is the lead sponsor of 137 studies on the registry; 37 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Newly diagnosed RA patients meeting American College of Rheumatology / European League Against Rheumatism 2010 classification criteria
  • Consecutive inpatients admitted during study period

Exclusion criteria

Exclusion Criteria:

  • Patients subsequently determined not to have RA
  • Incomplete clinical data preventing risk or treatment assessment
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Study design

Phase
Not applicable
Primary purpose
Health services research
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
100 participants (estimated)

Study arms

  • Experimental
    GenAI-Assisted RA Bone Erosion Risk Assessment and DMARD Selection

    This arm will include at least 100 consecutive adult inpatients with rheumatoid arthritis (RA) receiving routine clinical care. For each patient, the treating physician will first independently assess bone erosion risk and select a disease-modifying antirheumatic drug (DMARD) treatment strategy based on available clinical information (pre-AI assessment). The physician will then review a GenAI-generated clinical decision support report containing predicted bone erosion risk levels and DMARD recommendations and record an updated risk assessment and treatment decision (post-AI assessment). Pre-AI and post-AI physician decisions will be compared against independent expert reference standards to evaluate the impact of GenAI-assisted decision support. Treating physicians retain full responsibility for final clinical decisions.

    Other: GenAI-Assisted Clinical Decision Support for RABER Assessment and DMARD Selection

Interventions

  • OtherGenAI-Assisted Clinical Decision Support for RABER Assessment and DMARD Selection

    The intervention consists of a GenAI-generated clinical decision support report provided to treating physicians during routine RA care. Using patient clinical information available at the time of assessment, the GenAI system generates predicted bone erosion risk probabilities (0-100%), risk levels (0-3), and DMARD treatment recommendations. Physicians review the report after completing their independent pre-AI assessments and may revise their risk assessments and treatment decisions based on the additional information. The GenAI system provides decision support only and does not autonomously make or implement treatment decisions.

06

What researchers measure

Primary outcomes

  1. Percentage of Participants With a Change in Physician-Assessed Rheumatoid Arthritis Bone Erosion Risk Level After GenAI-Assisted Decision Support

    The percentage of participants for whom the treating physician changes the rheumatoid arthritis bone erosion risk level after reviewing the GenAI-generated clinical decision support report, compared with the initial assessment before reviewing the report. Risk levels are categorized from 0 to 3. A change is defined as any difference between the pre-AI and post-AI risk levels. The percentage is calculated using participants with complete paired assessments.

    Time frame: During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)

  2. Cohen's Kappa Agreement Between Physician-Assessed Rheumatoid Arthritis Bone Erosion Risk Levels and the Reference Standard Before and After GenAI-Assisted Decision Support

    Agreement between physician-assessed rheumatoid arthritis bone erosion risk levels (0-3) and the reference standard will be evaluated separately before and after review of the GenAI report using Cohen's kappa coefficient. The pre-AI and post-AI kappa coefficients will be compared to assess changes in agreement following GenAI-assisted decision support. Cohen's kappa ranges from -1 to 1, with higher values indicating greater agreement beyond chance. The difference between post-AI and pre-AI kappa coefficients will be reported, with positive values indicating improved agreement. The reference classification will be established during the data analysis stage by three independent expert physicians who are not involved in patient treatment, with disagreements resolved through consensus.

    Time frame: During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)

Secondary outcomes

  1. Cohen's Kappa Agreement Between Physician DMARD Treatment Selection Categories and the Reference Standard After GenAI-Assisted Decision Support

    Agreement between physician-selected disease-modifying antirheumatic drug (DMARD) treatment categories (0-4) and the reference standard will be assessed after physicians review the GenAI-generated clinical decision support report. Agreement will be quantified using Cohen's kappa coefficient, with higher values indicating greater agreement beyond chance. The analysis will include participants with complete post-AI physician treatment selections and corresponding reference standard classifications. The reference classification will be established during the data analysis stage by three independent expert physicians who are not involved in patient treatment, with disagreements resolved through consensus.

    Time frame: During index hospitalization, after physician review of the GenAI report (approximately 1-7 days)

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Study locations

1 of 1 sites recruiting
  • Guang'anmen Hospital of China Academy of Chinese Medical Sciences
    Beijing, Beijing Municipality 100053, China
    Recruiting
    • Quan Jiang, MD · Contactdoctorjq@126.com · 010-88001942
    • Quan Jiang, MD · Principal investigator
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References and documents

Individual participant data

Plan to share: No

No publications or documents are linked to this record.

09

Updates

1 registry update since Sep 25, 2026
Registered
First appeared on the registry. No changes since
Nov 4, 2026
Show all 1 update
  1. Nov 4, 2026
    First appeared on the registry

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT07914907
Responsible party
Quan Jiang (Director of the Rheumatology Department, Guang'anmen Hospital of China Academy of Chinese Medical Sciences) — Principal investigator
First posted
Nov 4, 2026
Start date
Mar 1, 2026
Primary completion
Oct 31, 2026 (estimated)
Completion
Dec 31, 2026 (estimated)
Last update
Nov 4, 2026

Study contacts

Quan Jiang, MD
Contact
doctorjq@126.com
010-88001942

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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