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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.

Studieoversikt

Status

Rekruttering

Forhold

Intervensjon / Behandling

Studietype

Intervensjonell

Registrering (Antatt)

100

Fase

  • Ikke aktuelt

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

Studiesteder

    • Beijing Municipality
      • Beijing, Beijing Municipality, Kina, 100053
        • Rekruttering
        • Guang'anmen Hospital of China Academy of Chinese Medical Sciences
        • Ta kontakt med:
        • Hovedetterforsker:
          • Quan Jiang, MD

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

18 år og eldre (Voksen, Eldre voksen)

Tar imot friske frivillige

Nei

Kjønn som er kvalifisert for studier

Alle

Beskrivelse

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

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Helsetjenesteforskning
  • Tildeling: N/A
  • Intervensjonsmodell: Enkeltgruppeoppdrag
  • Masking: Ingen (Open Label)

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Eksperimentell: 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.

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Percentage of Participants With a Change in Physician-Assessed Rheumatoid Arthritis Bone Erosion Risk Level After GenAI-Assisted Decision Support
Tidsramme: During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)

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

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Cohen's Kappa Agreement Between Physician DMARD Treatment Selection Categories and the Reference Standard After GenAI-Assisted Decision Support
Tidsramme: During index hospitalization, after physician review of the GenAI report (approximately 1-7 days)

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)

Samarbeidspartnere og etterforskere

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Sponsor

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Faktiske)

1. mars 2026

Primær fullføring (Antatt)

31. oktober 2026

Studiet fullført (Antatt)

31. desember 2026

Datoer for studieregistrering

Først innsendt

21. oktober 2026

Først innsendt som oppfylte QC-kriteriene

28. oktober 2026

Først lagt ut (Faktiske)

4. november 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

4. november 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

28. oktober 2026

Sist bekreftet

1. oktober 2026

Mer informasjon

Begreper knyttet til denne studien

Andre studie-ID-numre

  • 2026-667-KY-01-raber1
  • CI2023C019YL (Annet stipend/finansieringsnummer: China Academy of Chinese Medical Sciences)
  • CI2026A01501 (Annet stipend/finansieringsnummer: China Academy of Chinese Medical Sciences)
  • HLCMHPP2023087 (Annet stipend/finansieringsnummer: China National Administration of Traditional Chinese Medicine)
  • 82230121 (Annet stipend/finansieringsnummer: National Natural Science Foundation of China)

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

NEI

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

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