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GenAI-Assisted Rheumatoid Arthritis Bone Erosion Risk Assessment and DMARD Selection (RABER)
Prospective Evaluation of Generative AI-Augmented Clinical Decision-Making for Rheumatoid Arthritis Bone Erosion Risk (RABER) Assessment and DMARD Selection in Routine Care
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.
Studie Overzicht
Toestand
Conditie
Interventie / Behandeling
Studietype
Inschrijving (Geschat)
Fase
- Niet toepasbaar
Contacten en locaties
Studiecontact
- Naam: Quan Jiang, MD
- Telefoonnummer: 010-88001942
- E-mail: doctorjq@126.com
Studie Locaties
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Beijing Municipality
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Beijing, Beijing Municipality, China, 100053
- Werving
- Guang'anmen Hospital of China Academy of Chinese Medical Sciences
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Contact:
- Quan Jiang, MD
- Telefoonnummer: 010-88001942
- E-mail: doctorjq@126.com
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Hoofdonderzoeker:
- Quan Jiang, MD
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-
Deelname Criteria
Geschiktheidscriteria
Leeftijden die in aanmerking komen voor studie
Accepteert gezonde vrijwilligers
Geslachten die in aanmerking komen voor studie
Beschrijving
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:
- Patients subsequently determined not to have RA
- Incomplete clinical data preventing risk or treatment assessment
Studie plan
Hoe is de studie opgezet?
Ontwerpdetails
- Primair doel: Onderzoek naar gezondheidsdiensten
- Toewijzing: NVT
- Interventioneel model: Opdracht voor een enkele groep
- Masker: Geen (open label)
Wapens en interventies
Deelnemersgroep / Arm |
Interventie / Behandeling |
|---|---|
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Experimenteel: 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. |
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. |
Wat meet het onderzoek?
Primaire uitkomstmaten
Uitkomstmaat |
Maatregel Beschrijving |
Tijdsspanne |
|---|---|---|
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Percentage of Participants With a Change in Physician-Assessed Rheumatoid Arthritis Bone Erosion Risk Level After GenAI-Assisted Decision Support
Tijdsspanne: During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)
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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. |
During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)
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Cohen's Kappa Agreement Between Physician-Assessed Rheumatoid Arthritis Bone Erosion Risk Levels and the Reference Standard Before and After GenAI-Assisted Decision Support
Tijdsspanne: During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)
|
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. |
During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)
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Secundaire uitkomstmaten
Uitkomstmaat |
Maatregel Beschrijving |
Tijdsspanne |
|---|---|---|
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Cohen's Kappa Agreement Between Physician DMARD Treatment Selection Categories and the Reference Standard After GenAI-Assisted Decision Support
Tijdsspanne: During index hospitalization, after physician review of the GenAI report (approximately 1-7 days)
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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. |
During index hospitalization, after physician review of the GenAI report (approximately 1-7 days)
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Medewerkers en onderzoekers
Studie record data
Bestudeer belangrijke data
Studie start (Werkelijk)
Primaire voltooiing (Geschat)
Studie voltooiing (Geschat)
Studieregistratiedata
Eerst ingediend
Eerst ingediend dat voldeed aan de QC-criteria
Eerst geplaatst (Werkelijk)
Updates van studierecords
Laatste update geplaatst (Werkelijk)
Laatste update ingediend die voldeed aan QC-criteria
Laatst geverifieerd
Meer informatie
Termen gerelateerd aan deze studie
Trefwoorden
Aanvullende relevante MeSH-voorwaarden
Andere studie-ID-nummers
- 2026-667-KY-01-raber1
- CI2023C019YL (Ander subsidie-/financieringsnummer: China Academy of Chinese Medical Sciences)
- CI2026A01501 (Ander subsidie-/financieringsnummer: China Academy of Chinese Medical Sciences)
- HLCMHPP2023087 (Ander subsidie-/financieringsnummer: China National Administration of Traditional Chinese Medicine)
- 82230121 (Ander subsidie-/financieringsnummer: National Natural Science Foundation of China)
Plan Individuele Deelnemersgegevens (IPD)
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