Orbital NeoplasmsNCT05645341
Artificial Intelligence-assisted Screening of Malignant Pigmented Tumors on the Ocular Surface
An observational study of Orbital Neoplasms and Conjunctival Neoplasms, run by Sun Yat-sen University at 1 site in China.
Trial summary
Rare diseases generally refer to diseases whose prevalence rate is lower than 1 / 10 000 and the number of patients is less than 140000. Rare diseases are generally faced with the dilemma of a lack of qualified doctors, difficulty in large-scale screening, and a lack of rapid and effective channels for medical… Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Orbital Neoplasms, Conjunctival Neoplasms, Eye Neoplasms
- What is being tested?
- screening system for ocular surface malignant tumors
- How many people
- 535 participants
- Where
- 1 siteChina
- Study dates
- 5 Dec 2022to 5 Jun 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Through the offline specialist clinics, online popular science, news reports, and other channels, we will promote and inform the crowd about the relevant knowledge of pigmented tumors on the ocular surface, so that they can judge by themselves that they are eligible to join the group, and freely decide whether to participate in this study or not.
Who may be able to join
- Dark-brown lesions on the ocular surface are found: i.e. ocular surface malignant melanoma, ocular basal cell carcinoma, conjunctival nevus, eyelid nevus, sclera pigmentation, benign eyelid keratosis
Who cannot join
- Non-pigmented ocular surface tumors: pterygium, corneal dermoid tumor, meibomian gland cyst, cataract, blepharitis, etc.
- The image quality does not meet the clinical requirements.
Trial locations and contacts
1 site in 1 country.
China1 site
Zhognshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, 510060
About this study
Rare diseases generally refer to diseases whose prevalence rate is lower than 1 / 10 000 and the number of patients is less than 140000. Rare diseases are generally faced with the dilemma of a lack of qualified doctors, difficulty in large-scale screening, and a lack of rapid and effective channels for medical treatment. Studies have shown that 42% of patients say they have been misdiagnosed, and each patient with a rare disease needs to go through an average of eight doctors in seven years to see a corresponding rare disease specialist. More importantly, most rare diseases seriously affect the health and quality of life of patients. The ocular surface malignant tumor is a typical rare disease, and its incidence is less than 1 / 100000. The ocular surface not only affects the patient's appearance, but also damages the visual function, and the malignant tumor may even affect life. These uncommon malignant tumors are often hidden in the common black nevus on the eye surface, which is easy to be ignored and has great potential risks. With the improvement of people's living standards, people start to pay attention to rare diseases.
In recent years, the rapid development of digital technology has also provided new opportunities for the prevention and treatment of rare diseases. Our team established the database of rare ophthalmopathy in China in the early stage, which provided a solid foundation for the digitization of precious clinical data. This study intends to develop an intelligent screening system for ocular surface malignant tumors, using the mobile phone for real-world verification and scale screening, and explore it to improve the ability of doctors to diagnose and treat rare diseases. This study is expected to improve the ability to screen malignant tumors on the ocular surface and provide a novel model for the universal screening of rare diseases.
- Conditions
- Orbital Neoplasms, Conjunctival Neoplasms, Eye Neoplasms
- Being tested
- screening system for ocular surface malignant tumors
- Keywords
- Mobile health, Artificaial intelligence medicine, Ocular surface malignant tumor
- Medical subject headings
- Orbital Neoplasms, Conjunctival Neoplasms, Eye Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
screening system for ocular surface malignant tumorsDiagnostic test
Develop an intelligent screening system for ocular surface malignant tumors, apply it to the mobile terminal for real-world verification and large-scale general screening, and test its effect on assisting doctors in the diagnosis and treatment of rare diseases.
| Study group | Role | What they receive |
|---|---|---|
| Eligible participants for smartphone-based ocular surface tumors diagnosis | Not described Receives: Diagnostic Test: screening system for ocular surface malignant tumors |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area under the curve (AUC)
Measure of the ability of a binary classifier to distinguish between malignent and benign.
Measured: 2024.1
Secondary outcomes (4)
Sensitivity, specificity and accuracy
The study will assess the sensitivity and specificity of the CaptureTumor (CaT) system under various conditions.
Measured: 2024.1
Screening coverage
Count the number of people who have successfully received and read knowledge about ocular surface pigmented tumors on each offline and online platform.
Measured: 2024.1
Referral efficiency
For cases where the system judges that it is necessary to go to the hospital for further diagnosis and treatment, two or more researchers will conduct a diagnostic review first. If further diagnosis and treatment is really needed, the subject will be contacted and told to go to the hospital for treatment by phone, text message, etc., and continue to follow up. Finally, the duration of diagnosis (screening time to pathological diagnosis time), visit distance, number of visits before diagnosis, and the proportion of referred patients in all subjects were counted.
Measured: 2024.1
Human-machine collaboration performance
Doctors with different seniority were asked to diagnose the test set with and without assistance from the intelligent screening system, and the accuracy in the two cases were calculated and compared.
Measured: 2024.1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Dec 2022
- Study start5 Dec 2022
- Primary completion5 Jun 2023
- Study completion5 Jun 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Orbital NeoplasmsStudies of the same condition, open and under way.
- More trials run by Sun Yat-sen UniversityThe 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 535 participants (actual)
Sponsor and investigators
- Lead sponsor
- Sun Yat-sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Haotian Lin, Sun Yat-sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05645341
- Sponsor's protocol ID
- 2022KYPJ067
- Status last verified
- Aug 2024
- First submitted
- 2 Dec 2022
- Last updated
- 5 Aug 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Wang R, Bi S, Lin D, Li M, Zhao L, Zhou Y, Jin L, Chen W, Li R, Shang Y, Yang H, Chen R, Xiao W, Ai S, Li J, Ling S, Wu X, Li Z, Liu G, Lu Y, Lin W, Rao H, Meng X, Yan H, Nie C, Zhu M, Ye H, Lin H. Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies: A Nonrandomized Clinical Trial. JAMA Ophthalmol. 2026 Jul 1;144(7):627-635. doi: 10.1001/jamaophthalmol.2026.1609.
PubMed 42240998
Study at a glance
From the registry record, last updated by the sponsor on 5 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence-assisted Screening of Malignant Pigmented Tumors on the Ocular Surface
- ClinicalTrials.gov ID
- NCT05645341
- Acronym / sponsor ID
- 2022KYPJ067
- Conditions
- Orbital Neoplasms, Conjunctival Neoplasms, Eye Neoplasms
- Keywords
- Mobile health, Artificaial intelligence medicine, Ocular surface malignant tumor
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 535 participants (actual)
- Lead sponsor
- Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 5 Dec 2022 (actual)
- Primary completion
- 5 Jun 2023 (actual)
- Study completion
- 5 Jun 2023 (actual)
- First posted
- 9 Dec 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Rare diseases generally refer to diseases whose prevalence rate is lower than 1 / 10 000 and the number of patients is less than 140000. Rare diseases are generally faced with the dilemma of a lack of qualified doctors, difficulty in large-scale screening, and a lack of rapid and effective channels for medical treatment. Studies have shown that 42% of patients say they have been misdiagnosed, and each patient with a rare disease needs to go through an average of eight doctors in seven years to see a corresponding rare disease specialist. More importantly, most rare diseases seriously affect the health and quality of life of patients. The ocular surface malignant tumor is a typical rare disease, and its incidence is less than 1 / 100000. The ocular surface not only affects the patient's appearance, but also damages the visual function, and the malignant tumor may even affect life. These uncommon malignant tumors are often hidden in the common black nevus on the eye surface, which is easy to be ignored and has great potential risks. With the improvement of people's living standards, people start to pay attention to rare diseases.
In recent years, the rapid development of digital technology has also provided new opportunities for the prevention and treatment of rare diseases. Our team established the database of rare ophthalmopathy in China in the early stage, which provided a solid foundation for the digitization of precious clinical data. This study intends to develop an intelligent screening system for ocular surface malignant tumors, using the mobile phone for real-world verification and scale screening, and explore it to improve the ability of doctors to diagnose and treat rare diseases. This study is expected to improve the ability to screen malignant tumors on the ocular surface and provide a novel model for the universal screening of rare diseases.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Eligible participants for smartphone-based ocular surface tumors diagnosis | – | Diagnostic Test: screening system for ocular surface malignant tumors |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Through the offline specialist clinics, online popular science, news reports, and other channels, we will promote and inform the crowd about the relevant knowledge of pigmented tumors on the ocular surface, so that they can judge by themselves that they are eligible to join the group, and freely decide whether to participate in this study or not.
Key inclusion criteria (1 listed)
- Dark-brown lesions on the ocular surface are found: i.e. ocular surface malignant melanoma, ocular basal cell carcinoma, conjunctival nevus, eyelid nevus, sclera pigmentation, benign eyelid keratosis
Key exclusion criteria (2 listed)
- Non-pigmented ocular surface tumors: pterygium, corneal dermoid tumor, meibomian gland cyst, cataract, blepharitis, etc.
- The image quality does not meet the clinical requirements.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| screening system for ocular surface malignant tumorsDevelop an intelligent screening system for ocular surface malignant tumors, apply it to the mobile terminal for real-world verification and large-scale general screening, and test its effect on assisting doctors in the diagnosis and treatment of rare diseases. | Diagnostic test | Eligible participants for smartphone-based ocular surface tumors diagnosis |
Primary outcome
Area under the curve (AUC)
Time frame: 2024.1
Measure of the ability of a binary classifier to distinguish between malignent and benign.
4 secondary outcomes
Sensitivity, specificity and accuracy
Time frame: 2024.1
Screening coverage
Time frame: 2024.1
Referral efficiency
Time frame: 2024.1
Human-machine collaboration performance
Time frame: 2024.1
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Aug 2024.
- Derived from this study: PubMed 42240998Wang R, Bi S, Lin D, Li M, Zhao L, Zhou Y, Jin L, Chen W, Li R, Shang Y, Yang H, Chen R, Xiao W, Ai S, Li J, Ling S, Wu X, Li Z, Liu G, Lu Y, Lin W, Rao H, Meng X, Yan H, Nie C, Zhu M, Ye H, Lin H. Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies: A Nonrandomized Clinical Trial. JAMA Ophthalmol. 2026 Jul 1;144(7):627-635. doi: 10.1001/jamaophthalmol.2026.1609.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Orbital Neoplasms and Conjunctival Neoplasms, run by Sun Yat-sen University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 Aug 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Area under the curve (AUC) (time frame: 2024.1). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05645341, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Aug 2024.