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NCT Number: NCT07650799

AI-assisted Rare Disease Diagnosis

A multicentre randomised controlled trial evaluating whether a rare-disease diagnostic large language model can improve diagnostic quality, efficiency, and health-economic outcomes for physicians managing patients with suspected rare or diagnostically unresolved disease.

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Key information

Age range

0 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Peking Union Medical College Hospital, Beijing, China

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About this study

Rare disease patients commonly experience prolonged diagnostic odysseys rooted in limited rare disease recognition, phenotypic heterogeneity, and dispersed diagnostic clues. Diagnostic decision-support large language models may improve first-visit consultations by integrating prior records, generating structured analyses, and proposing candidate diagnoses, thereby shortening diagnostic pathways and improving appropriate genetic testing referral.

Participating physicians will provide care under both AI-assisted and standard diagnostic workflows. Eligible patients will be individually randomised to receive either AI-assisted diagnostic support or standard clinical practice.

In the intervention arm, physicians will have diagnostic support from AI when seeing patients. In the control arm, patients are seen under standard hospital workflow without any generative AI tools. Outcomes adjudicated by an independent Expert Committee blinded to arm assignment; adjudicators access no AI-generated materials.

A prospective within-trial economic evaluation will be conducted alongside the randomized trial. Healthcare resource use and costs associated with the diagnostic pathway will be collected.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Patient Inclusion Criteria:

  • Any age. Legal guardian co-signs consent for minors or individuals lacking legal capacity.
  • Diagnostically unresolved or suspected rare disease, with at least one prior complete clinical evaluation at a secondary-level or higher institution yielding no confirmed explanatory diagnosis.
  • First presentation to the enrolling institution for the current condition, with no prior records in the institutional HIS or outpatient system.
  • No prior genetic testing related to the current condition; no results or reports available.
  • Written informed consent provided voluntarily by patient or legal guardian, with commitment and ability to complete structured follow-up.

Patient Exclusion Criteria:

  • Confirmed diagnosis (clinical, pathological, or molecular) explaining the primary symptoms.
  • Emergency presentation, critical illness, or any condition incompatible with trial participation.
  • Neither patient nor legally authorised proxy able to complete follow-up.
  • Concurrent enrollment in another interventional study with diagnostic accuracy or genetic testing yield as a primary endpoint.
  • Prior use of another AI system has already yielded a confirmed diagnosis for the current condition.

Physician Inclusion Criteria

  • Licensed physician in internal medicine, neurology, pediatrics, general medicine, rare disease, or a related specialty.
  • ≥2 years of clinical practice; competent to manage rare disease patients; stratified into junior or senior tier.
  • Voluntary participation with written informed consent.

Physician Exclusion Criteria

  • No longer in clinical practice, or unable to fulfill required outpatient duties during the study period.
  • Unwilling to provide informed consent or to permit protocol-required collection of consultation and questionnaire data.
  • Currently enrolled in another AI-assisted clinical workflow, or expected to be unable to comply with the procedures.

Treatment and study plan

AI system

Other

The study AI system will be used to provide diagnostic support during the clinical encounter, including structuring relevant clinical information, generating a clinical analysis, and suggesting candidate diagnoses for review by the treating physician.

Primary outcomes

  1. Overall Correct Diagnostic Yield

    Time frame: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.

    The proportion of all randomised patients whose clinical diagnosis by the end of follow-up is concordant with the blinded-adjudicated final reference diagnosis determined by an independent committee.

Secondary outcomes

  1. Candidate Diagnostic Accuracy

    Time frame: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.

    The agreement between physician-provided candidate diagnoses in the the initial consultation and the independently adjudicated reference diagnosis.

  2. Molecular Diagnostic Yield

    Time frame: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.

    The proportion of all randomized patients in whom genetic testing performed as part of the clinical diagnostic pathway identifies a clinically relevant molecular finding that is confirmed through independent genetics review.

  3. Time to a Correct Diagnosis

    Time frame: From enrollment to the end of follow-up, up to 8 weeks.

    The number of days from the first study visit to the first physician-assigned diagnosis that is subsequently confirmed as concordant with the independently adjudicated reference diagnosis.

  4. Appropriate Genetic Testing Recommendation Rate

    Time frame: From the initial consultation to genetic testing indication adjudication, approximately 8 weeks

    The proportion of randomized patients for whom physician-recommended genetic testing is concordant with the indication determined by an independent genetics adjudication committee.

  5. Duration of the Initial Physician Consultation

    Time frame: Assessed at each consultation (day 1), within 1 day.

    In-room consultation time will be recorded, measured, and compared between arms.

  6. Physician-Reported Experience

    Time frame: Assessed at each consultation (day 1), within 1 day.

    Physicians will assess their experience of the diagnostic workflow. Responses will be recorded using a standardized rating scale (range 1-5, where higher scores indicate more positive experience).

  7. Patient-Reported Experience

    Time frame: Assessed at each consultation (day 1), within 1 day.

    Patients will assess their experience of the diagnostic workflow. Responses will be recorded using a standardized rating scale (range 1-5, where higher scores indicate more positive experience).

Study contacts

Contact information is provided by the study sponsor or research team.

Shuyang Zhang, MD, PhD

CONTACT

[email protected]

+86-13911667211

Sponsors and collaborators

Lead sponsor

Peking Union Medical College Hospital

Other

Collaborators

  • Cangzhou Central Hospital
  • Dongguan People's Hospital
  • First People's Hospital of Foshan
  • Guizhou Provincial People's Hospital
  • Qinghai People's Hospital
  • The First People's Hospital of Yunnan
  • Tianjin Children's Hospital
  • Zhangzhou Municipal Hospital

Registry information

Official study title

A Multicentre Randomised Controlled Trial of LLM-Assisted Diagnostic Support in Patients With Suspected Rare or Diagnostically Unresolved Disease

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Jun 16, 2026
Registry last updated
Jul 27, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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