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Artificial Intelligence for Rare Disease Diagnosis

3. Juni 2026 aktualisiert von: Shuyang Zhang, MD, PhD, Peking Union Medical College Hospital

A Multicentre, Randomised Diagnostic Accuracy Study Evaluating AI Assisted Diagnosis of Rare Diseases

A multicentre, randomised diagnostic accuracy study to evaluate whether the rare disease-specific AI can improve diagnostic accuracy and efficiency for physicians managing real-world clinical cases.

Studienübersicht

Status

Noch keine Rekrutierung

Bedingungen

Intervention / Behandlung

Detaillierte Beschreibung

Rare diseases collectively affect approximately 300 million individuals worldwide. This prolonged diagnostic delay is attributable in large part to the breadth of over 7,000 recognized rare conditions, which far exceeds the clinical exposure of any individual physician. A rare disease-specific diagnostic AI was developed by Peking Union Medical College Hospital (PUMCH), supporting differential diagnosis generation, clinical workup planning, and genomic variant interpretation. A balanced crossover design ensures that each enrolled physician serves as their own control, substantially reducing confounding from inter-reader variability in baseline diagnostic competency. Within each physician, cases are randomly assigned at the case level to either the AI-assisted or unassisted condition, such that each physician reads a subset of cases with AI assistance and the remaining cases without. This within-reader, case-level randomization eliminates the need for a washout period and directly controls for inter-reader differences in baseline diagnostic competency. All cases are collected from real-world clinical settings with independently confirmed gold-standard diagnoses and span a pre-specified spectrum of rare and non-rare disease categories, reflecting the differential diagnostic challenge encountered in routine clinical practice, to ensure diagnostic breadth and clinical representativeness. Physician seniority (junior vs. senior) is incorporated as a pre-specified stratification and subgroup analysis variable. Diagnostic outputs are evaluated by an independent Expert Adjudication Committee, blinded to the assistance condition, using standardized scoring criteria established prior to data collection.

Studientyp

Interventionell

Einschreibung (Geschätzt)

150

Phase

  • Unzutreffend

Kontakte und Standorte

Dieser Abschnitt enthält die Kontaktdaten derjenigen, die die Studie durchführen, und Informationen darüber, wo diese Studie durchgeführt wird.

Studienkontakt

Studienorte

  • China
      • Beijing, China
        • Peking Union Medical College Hospital
        • Kontakt:
      • Cangzhou, China
        • Cangzhou Central Hospital
        • Kontakt:
      • Changchun, China
        • Changchun Sacred Heart Hospital
        • Kontakt:
      • Dongguan, China
        • Dongguan People's Hospital
        • Kontakt:
      • Foshan, China
        • First People's Hospital of Foshan
        • Kontakt:
      • Guiyang, China
        • Guizhou Provincial People's Hospital
        • Kontakt:
      • Jilin City, China
        • Jilin Central General Hospital
        • Kontakt:
      • Kunming, China
        • The First People's Hospital of Yunnan Province
        • Kontakt:
          • Jianhong Hou
          • Telefonnummer: +86-0871-63638800
          • E-Mail: khyyyb@163.com
      • Lhasa, China
        • Tibet Autonomous Region People's Hospital
        • Kontakt:
      • Tianjin, China
        • Tianjin Children's Hospital
        • Kontakt:
      • Wuhai, China
        • Wuhai People's Hospital
        • Kontakt:
      • Xining, China
        • Qinghai Provincial People's Hospital
        • Kontakt:
      • Zhangzhou, China
        • Zhangzhou Municipal Hospital of Fujian Province
        • Kontakt:

Teilnahmekriterien

Forscher suchen nach Personen, die einer bestimmten Beschreibung entsprechen, die als Auswahlkriterien bezeichnet werden. Einige Beispiele für diese Kriterien sind der allgemeine Gesundheitszustand einer Person oder frühere Behandlungen.

Zulassungskriterien

Studienberechtigtes Alter

  • Erwachsene
  • Älterer Erwachsener

Akzeptiert gesunde Freiwillige

Ja

Beschreibung

Inclusion Criteria:

  • 1. Licensed physicians at the junior or senior level affiliated with internal medicine, neurology, pediatrics, and rare disease-related departments.
  • 2. Willingness to provide written informed consent, adhere to trial protocols, and complete all required pre-study training prior to enrollment.

Exclusion Criteria:

  • 1. Prior exposure to any of the clinical cases included in the study case library.
  • 2. Direct participation in the design or development of the AI model.

Studienplan

Dieser Abschnitt enthält Einzelheiten zum Studienplan, einschließlich des Studiendesigns und der Messung der Studieninhalte.

Wie ist die Studie aufgebaut?

Designdetails

  • Hauptzweck: Diagnose
  • Zuteilung: Zufällig
  • Interventionsmodell: Crossover-Aufgabe
  • Maskierung: Single

Waffen und Interventionen

Teilnehmergruppe / Arm
Intervention / Behandlung
Experimental: Intervention Arm
Physicians complete assigned diagnostic tasks with the assistance of AI system in addition to conventional clinical resources.
Sonstiges: AI-Assisted Diagnosis
A rare disease-specific diagnostic AI model is used to accept free text input and assist in rare disease diagnoses. During the experimental condition, physicians may interact with the system freely alongside standard clinical resources to support their diagnostic reasoning.
Kein Eingriff: Control Arm
Physicians complete the assigned diagnostic tasks using conventional clinical resources only (e.g., medical databases and literature), without access to any generative AI tools. This arm reflects routine clinical diagnostic practice.

Was misst die Studie?

Primäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Top-3 Diagnostic Accuracy
Zeitfenster: Up to 60 minutes per case (from case presentation to diagnostic report submission).
The percentage of definitive diagnosis is included within the physician's top 3 choices.
Up to 60 minutes per case (from case presentation to diagnostic report submission).

Sekundäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Diagnosis Time per Case
Zeitfenster: Up to 60 minutes per case (from case presentation to diagnostic report submission).
Elapsed time from initial case presentation to final diagnostic report submission, recorded automatically via system logs.
Up to 60 minutes per case (from case presentation to diagnostic report submission).
Workup Plan Quality
Zeitfenster: Up to 60 minutes per case (from case presentation to diagnostic report submission).
Quality score of the clinical workup plan assigned by an independent expert committee using a standardized Likert Scale. Scores range from 1 to 10, with higher scores indicating better workup plan quality.
Up to 60 minutes per case (from case presentation to diagnostic report submission).
Physician Reported Usability of the AI-Assisted Diagnostic System
Zeitfenster: Up to 60 minutes per case (upon completion of each case reading).
Physician-reported usability of the AI system, assessed after completion of each AI-assisted case reading using a 10-point physician-rated usability scale. Scores range from 1 to 10, with higher scores indicating better system usability.
Up to 60 minutes per case (upon completion of each case reading).
Physician Reported Workload
Zeitfenster: Up to 60 minutes per case (upon completion of each case reading).
Task-related workload experienced by physicians, assessed after completion of each AI-assisted case reading using a 10-point Physician Workload Likert scale. Scores range from 1 to 10, with higher scores indicating a higher workload.
Up to 60 minutes per case (upon completion of each case reading).
Physician Satisfaction
Zeitfenster: Up to 60 minutes per case (upon completion of each case reading).
Overall satisfaction of physicians with the diagnostic workflow, assessed after completion of each AI-assisted case reading using a 10-point Satisfaction Likert scale. Scores range from 1 to 10, with higher scores indicating higher satisfaction.
Up to 60 minutes per case (upon completion of each case reading).
Physician Intention to Adopt AI-Assisted Diagnostic Support
Zeitfenster: Up to 60 minutes per case (upon completion of each case reading).
Physician willingness to integrate AI system into routine clinical practice, assessed after completion of each AI-assisted case reading using a 10-point Adoption Intention Likert scale. Scores range from 1 to 10, with higher scores indicating higher adoption intention.
Up to 60 minutes per case (upon completion of each case reading).

Mitarbeiter und Ermittler

Hier finden Sie Personen und Organisationen, die an dieser Studie beteiligt sind.

Sponsor

Peking Union Medical College Hospital

Mitarbeiter

Guizhou Provincial People's Hospital
First People's Hospital of Foshan
Dongguan People's Hospital
Qinghai People's Hospital
Cangzhou Central Hospital
The First People's Hospital of Yunnan
Tibet Autonomous Region People's Hospital
Tianjin Children's Hospital
Zhangzhou Municipal Hospital of Fujian Province

Ermittler

  • Hauptermittler: Shuyang Zhang, Peking Union Medical College Hospital

Studienaufzeichnungsdaten

Diese Daten verfolgen den Fortschritt der Übermittlung von Studienaufzeichnungen und zusammenfassenden Ergebnissen an ClinicalTrials.gov. Studienaufzeichnungen und gemeldete Ergebnisse werden von der National Library of Medicine (NLM) überprüft, um sicherzustellen, dass sie bestimmten Qualitätskontrollstandards entsprechen, bevor sie auf der öffentlichen Website veröffentlicht werden.

Haupttermine studieren

Studienbeginn (Geschätzt)

20. Juni 2026

Primärer Abschluss (Geschätzt)

1. Dezember 2026

Studienabschluss (Geschätzt)

1. Juni 2027

Studienanmeldedaten

Zuerst eingereicht

28. Mai 2026

Zuerst eingereicht, das die QC-Kriterien erfüllt hat

3. Juni 2026

Zuerst gepostet (Tatsächlich)

4. Juni 2026

Studienaufzeichnungsaktualisierungen

Letztes Update gepostet (Tatsächlich)

4. Juni 2026

Letztes eingereichtes Update, das die QC-Kriterien erfüllt

3. Juni 2026

Zuletzt verifiziert

1. Juni 2026

Mehr Informationen

Begriffe im Zusammenhang mit dieser Studie

Schlüsselwörter

Zusätzliche relevante MeSH-Bedingungen

Andere Studien-ID-Nummern

  • PUMCH I-23PJ948

Arzneimittel- und Geräteinformationen, Studienunterlagen

Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt

Nein

Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt

Nein

Diese Informationen wurden ohne Änderungen direkt von der Website clinicaltrials.gov abgerufen. Wenn Sie Ihre Studiendaten ändern, entfernen oder aktualisieren möchten, wenden Sie sich bitte an register@clinicaltrials.gov. Sobald eine Änderung auf clinicaltrials.gov implementiert wird, wird diese automatisch auch auf unserer Website aktualisiert .

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