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.
調査の概要
状態
状態
条件
条件
介入・治療
介入・治療
研究の種類
研究の種類
入学 (推定)
入学
段階
段階
- 適用できない
連絡先と場所
研究連絡先
研究連絡先
- 名前：Quan Jiang, MD
- 電話番号：010-88001942
- メール：doctorjq@126.com
研究場所
-
-
Beijing Municipality
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Beijing、Beijing Municipality、中国、100053
- 募集
- Guang'anmen Hospital of China Academy of Chinese Medical Sciences
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コンタクト：
- Quan Jiang, MD
- 電話番号：010-88001942
- メール：doctorjq@126.com
-
主任研究者：
- Quan Jiang, MD
-
-
参加基準
適格基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
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
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：ヘルスサービス研究
- 割り当て：なし
- 介入モデル：単一グループの割り当て
- マスキング：なし（オープンラベル）
アーム数
武器と介入
参加者グループ / アーム参加者グループ / アーム |
介入・治療介入・治療 |
|---|---|
|
実験的：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. |
この研究は何を測定していますか？
主要な結果の測定
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Percentage of Participants With a Change in Physician-Assessed Rheumatoid Arthritis Bone Erosion Risk Level After GenAI-Assisted Decision Support
時間枠：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)
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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
時間枠：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)
|
二次結果の測定
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Cohen's Kappa Agreement Between Physician DMARD Treatment Selection Categories and the Reference Standard After GenAI-Assisted Decision Support
時間枠：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)
|
協力者と研究者
スポンサー
スポンサー
研究記録日
主要日程の研究
研究開始 (実際)
研究開始
一次修了 (推定)
一次修了
研究の完了 (推定)
研究の完了
試験登録日
最初に提出
最初に提出
QC基準を満たした最初の提出物
QC基準を満たした最初の提出物
最初の投稿 (実際)
最初の投稿
学習記録の更新
投稿された最後の更新 (実際)
投稿された最後の更新
QC基準を満たした最後の更新が送信されました
QC基準を満たした最後の更新が送信されました
最終確認日
最終確認日
詳しくは
本研究に関する用語
キーワード
その他の研究ID番号
その他の研究ID番号
- 2026-667-KY-01-raber1
- CI2023C019YL (その他の助成金/資金番号：China Academy of Chinese Medical Sciences)
- CI2026A01501 (その他の助成金/資金番号：China Academy of Chinese Medical Sciences)
- HLCMHPP2023087 (その他の助成金/資金番号：China National Administration of Traditional Chinese Medicine)
- 82230121 (その他の助成金/資金番号：National Natural Science Foundation of China)
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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