Rare DisordersNCT07650799
AI-assisted Rare Disease Diagnosis
A study testing AI system in people with Rare Disorders and Rare Diseases, run by Peking Union Medical College Hospital at 12 sites in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 0 years and older
- Conditions the study is for
- Rare Disorders, Rare Diseases
- What is being tested?
- AI system
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,056 participants
- Where
- 12 sitesChina
- Study dates
- 1 Aug 2026to 1 Dec 2027
- Phase
- Interventional
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 0 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
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.
Trial locations and contacts
12 sites in 1 country. Contact the study team or a site near you to ask about taking part.
12 sites in 1 country
China12 sites, 12 recruiting
- Not yet recruiting
Cangzhou Central Hospital
Cangzhou
Yong Li, +86-0317-2075013, czszxyyirb@163.com
- Not yet recruiting
Dongguan People's Hospital
Dongguan
Yaoqing Yuan, +86-0769-28637333, dgrmyyirb@163.com
- Not yet recruiting
First People's Hospital of Foshan
Foshan
Jun Jiang, +86-0757-83833633, jinye0320@163.com
- Not yet recruiting
Guizhou Provincial People's Hospital
Guiyang
Yan Zha, +86-0851-85937094, sytsb606@sina.com
- Recruiting
Jilin Central General Hospital
Jilin City
Mingyu Shao, +86-0432-62456181, jlszxyy@163.com
- Not yet recruiting
The First People's Hospital of Yunnan Province
Kunming
Jianhong Hou, +86-0871-63638800, khyyyb@163.com
- Not yet recruiting
Tianjin Children's Hospital
Tianjin
Wei Liu, 022-87787101, setyyyb@tj.gov.cn
- Recruiting
Tianshui 407 Hospital
Tianshui
Zhaoxiao Lu, +86-0938-8291992, ts407yy@sina.com
- Not yet recruiting
Tianshui 407 Hospital
Tianshui
Rong Sun, +86-0938-8229999, ts407yy@sina.com
- Not yet recruiting
Wuhai People's Hospital
Wuhai
Rui Ren, +86-0473-2035041, whsrmyybgs@163.com
- Recruiting
Qinghai Provincial People's Hospital
Xining
Qiang Zhang, +86-0971-8177911, 403252559@qq.com
- Not yet recruiting
Zhangzhou Municipal Hospital of Fujian Province
Zhangzhou
Xiao Yang, +86-0596-2082950, zzfh2005@126.com
About this study
Official title: A Multicentre Randomised Controlled Trial of LLM-Assisted Diagnostic Support in Patients With Suspected Rare or Diagnostically Unresolved Disease
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.
Read the detailed description
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.
- Conditions
- Rare Disorders, Rare Diseases
- Being tested
- AI system
- Keywords
- rare diseases, AI, LLM, diagnosis, cost-effectiveness
- Medical subject headings
- Rare Diseases, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI systemOther
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.
| Study group | Role | What they receive |
|---|---|---|
| AI system | Experimental | AI system will be used to provide diagnostic support during the encounter in addition to conventional clinical workflow. Use of other generative AI tools is prohibited. Receives: Other: AI system |
| Standard of care | No intervention | The physician conducts the encounter per standard hospital workflow using conventional clinical resources only. Use of any generative AI tool is prohibited. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Overall Correct Diagnostic Yield
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.
Measured: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.
Secondary outcomes (7)
Candidate Diagnostic Accuracy
The agreement between physician-provided candidate diagnoses in the the initial consultation and the independently adjudicated reference diagnosis.
Measured: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.
Molecular Diagnostic Yield
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.
Measured: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.
Time to a Correct Diagnosis
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.
Measured: From enrollment to the end of follow-up, up to 8 weeks.
Appropriate Genetic Testing Recommendation Rate
The proportion of randomized patients for whom physician-recommended genetic testing is concordant with the indication determined by an independent genetics adjudication committee.
Measured: From the initial consultation to genetic testing indication adjudication, approximately 8 weeks
Duration of the Initial Physician Consultation
In-room consultation time will be recorded, measured, and compared between arms.
Measured: Assessed at each consultation (day 1), within 1 day.
Physician-Reported Experience
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).
Measured: Assessed at each consultation (day 1), within 1 day.
Patient-Reported Experience
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).
Measured: Assessed at each consultation (day 1), within 1 day.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Jun 2026
- Study start1 Aug 2026
- Primary completion1 Jul 2027 (estimated)
- Study completion1 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Rare DisordersStudies of the same condition, open and under way.
- More trials run by Peking Union Medical College HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- This is a multicentre, prospective, parallel controlled study. Eligible patients will be assigned to either an AI-assisted diagnostic workflow or a standard diagnostic workflow. Participating physicians will provide care under both study conditions.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 1,056 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Peking Union Medical College Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Cangzhou Central Hospital, Zhangzhou Municipal Hospital, Dongguan People's Hospital, First People's Hospital of Foshan, Guizhou Provincial People's Hospital, Tianjin Children's Hospital, The First People's Hospital of Yunnan, Qinghai People's Hospital, Tianshui 407 Hospital, Jilin city central hospital
- Responsible party
- Principal investigator, Shuyang Zhang, MD, PhD, Peking Union Medical College Hospital
- Investigators
- Shuyang Zhang, MD, PhD, Principal investigator, Peking Union Medical College Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07650799
- Sponsor's protocol ID
- PUMCH I-26PJ0002
- Status last verified
- Oct 2026
- First submitted
- 7 Jun 2026
- Last updated
- 13 Oct 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified IPD will be shared with qualified researchers upon reasonable request, subject to ethics approval and a data use agreement.