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.
Aperçu de l'étude
Statut
Statut
Les conditions
Les conditions
Intervention / Traitement
Intervention / Traitement
Type d'étude
Type d'étude
Inscription (Estimé)
Inscription
Phase
Phase
- N'est pas applicable
Contacts et emplacements
Coordonnées de l'étude
Coordonnées de l'étude
- Nom: Quan Jiang, MD
- Numéro de téléphone: 010-88001942
- E-mail: doctorjq@126.com
Lieux d'étude
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Beijing Municipality
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Beijing, Beijing Municipality, Chine, 100053
- Recrutement
- Guang'anmen Hospital of China Academy of Chinese Medical Sciences
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Contact:
- Quan Jiang, MD
- Numéro de téléphone: 010-88001942
- E-mail: doctorjq@126.com
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Chercheur principal:
- Quan Jiang, MD
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-
Critères de participation
Critère d'éligibilité
Critère d'éligibilité
Âges éligibles pour étudier
Accepte les volontaires sains
Sexes éligibles pour l'étude
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
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)
Nombre de bras
Armes et Interventions
Groupe de participants / BrasGroupe de participants / Bras |
Intervention / TraitementIntervention / Traitement |
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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
Principaux critères de jugement
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
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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)
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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
Délai: During index hospitalization, at pre-AI and post-AI physician assessments (approximately 1-7 days)
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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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Mesures de résultats secondaires
Mesures de résultats secondaires
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
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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)
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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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Collaborateurs et enquêteurs
Parrainer
Parrainer
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude (Réel)
Début de l'étude
Achèvement primaire (Estimé)
Achèvement primaire
Achèvement de l'étude (Estimé)
Achèvement de l'étude
Dates d'inscription aux études
Première soumission
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première soumission répondant aux critères de contrôle qualité
Première publication (Réel)
Première publication
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour publiée
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Dernière vérification
Plus d'information
Termes liés à cette étude
Mots clés
Termes MeSH pertinents supplémentaires
Autres numéros d'identification d'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)
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Informations sur les médicaments et les dispositifs, documents d'étude
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