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

28 octobre 2026 mis à jour par: Quan Jiang, Guang'anmen Hospital of China Academy of Chinese Medical Sciences

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.

Aperçu de l'étude

Statut

Recrutement

Les conditions

Intervention / Traitement

Type d'étude

Interventionnel

Inscription (Estimé)

100

Phase

  • N'est pas applicable

Contacts et emplacements

Cette section fournit les coordonnées de ceux qui mènent l'étude et des informations sur le lieu où cette étude est menée.

Coordonnées de l'étude

  • Nom: Quan Jiang, MD
  • Numéro de téléphone: 010-88001942
  • E-mail: doctorjq@126.com

Lieux d'étude

    • Beijing Municipality
      • Beijing, Beijing Municipality, Chine, 100053
        • Recrutement
        • Guang'anmen Hospital of China Academy of Chinese Medical Sciences
        • Contact:
        • Chercheur principal:
          • Quan Jiang, MD

Critères de participation

Les chercheurs recherchent des personnes qui correspondent à une certaine description, appelée critères d'éligibilité. Certains exemples de ces critères sont l'état de santé général d'une personne ou des traitements antérieurs.

Critère d'éligibilité

Âges éligibles pour étudier

18 ans et plus (Adulte, Adulte plus âgé)

Accepte les volontaires sains

Non

Sexes éligibles pour l'étude

Tout

La description

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

Plan d'étude

Cette section fournit des détails sur le plan d'étude, y compris la façon dont l'étude est conçue et ce que l'étude mesure.

Comment l'étude est-elle conçue ?

Détails de conception

  • Objectif principal: Recherche sur les services de santé
  • Répartition: N / A
  • Modèle interventionnel: Affectation à un seul groupe
  • Masquage: Aucun (étiquette ouverte)

Armes et Interventions

Groupe de participants / Bras
Intervention / Traitement
Expérimental: 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.

Que mesure l'étude ?

Principaux critères de jugement

Mesure des résultats
Description de la mesure
Délai
Percentage of Participants With a Change in Physician-Assessed Rheumatoid Arthritis Bone Erosion Risk Level After GenAI-Assisted Decision Support
Délai: 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
Délai: 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)

Mesures de résultats secondaires

Mesure des résultats
Description de la mesure
Délai
Cohen's Kappa Agreement Between Physician DMARD Treatment Selection Categories and the Reference Standard After GenAI-Assisted Decision Support
Délai: 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)

Collaborateurs et enquêteurs

C'est ici que vous trouverez les personnes et les organisations impliquées dans cette étude.

Parrainer

Dates d'enregistrement des études

Ces dates suivent la progression des dossiers d'étude et des soumissions de résultats sommaires à ClinicalTrials.gov. Les dossiers d'étude et les résultats rapportés sont examinés par la Bibliothèque nationale de médecine (NLM) pour s'assurer qu'ils répondent à des normes de contrôle de qualité spécifiques avant d'être publiés sur le site Web public.

Dates principales de l'étude

Début de l'étude (Réel)

1 mars 2026

Achèvement primaire (Estimé)

31 octobre 2026

Achèvement de l'étude (Estimé)

31 décembre 2026

Dates d'inscription aux études

Première soumission

21 octobre 2026

Première soumission répondant aux critères de contrôle qualité

28 octobre 2026

Première publication (Réel)

4 novembre 2026

Mises à jour des dossiers d'étude

Dernière mise à jour publiée (Réel)

4 novembre 2026

Dernière mise à jour soumise répondant aux critères de contrôle qualité

28 octobre 2026

Dernière vérification

1 octobre 2026

Plus d'information

Termes liés à cette étude

Autres numéros d'identification d'étude

  • 2026-667-KY-01-raber1
  • CI2023C019YL (Autre subvention/numéro de financement: China Academy of Chinese Medical Sciences)
  • CI2026A01501 (Autre subvention/numéro de financement: China Academy of Chinese Medical Sciences)
  • HLCMHPP2023087 (Autre subvention/numéro de financement: China National Administration of Traditional Chinese Medicine)
  • 82230121 (Autre subvention/numéro de financement: National Natural Science Foundation of China)

Plan pour les données individuelles des participants (IPD)

Prévoyez-vous de partager les données individuelles des participants (DPI) ?

NON

Informations sur les médicaments et les dispositifs, documents d'étude

Étudie un produit pharmaceutique réglementé par la FDA américaine

Non

Étudie un produit d'appareil réglementé par la FDA américaine

Non

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