MyopiaNCT06633393
Effect of a Myopia Prediction System on Myopia Prevention and Control
A study testing Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System and Feedback on Ophthalmic Examinations in people with Myopia and Randomized Controlled Trials, run by Zhongshan Ophthalmic Center, Sun Yat-sen University at 1 site in China.
Trial summary
The global rise in myopia, particularly among children and adolescents in China, underscores the inadequacy of current prevention strategies, indicating that conventional screening and education alone are insufficient to curb the prevalence. Read more about this study
- Who is it for?
- Ages 9 to 11 yearsHealthy volunteers can take part
- Conditions the study is for
- Myopia, Randomized Controlled Trials, Artificial Intelligence (AI)
- What is being tested?
- Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System and Feedback on Ophthalmic Examinations
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 20,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Nov 2024to 28 Feb 2026
- Phase
- Interventional
- 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 9 to 11 years
- All sexes
- Healthy volunteers accepted
- Child
Who may be able to join
- The participant and their guardian voluntarily signed the informed consent form
- Has the record of eye refraction examination in the past year
- Aged 9 to 11 years, regardless of gender
Who cannot join
- High myopia(spherical equivalent ≤ -6.00 D)
- Ocular diseases other than myopia (e.g., strabismus, amblyopia, congenital cataract, juvenile glaucoma, retinal diseases).
- Systemic diseases that may affect vision or visual development (e.g., diabetes or other endocrine disorders, cardiovascular or respiratory diseases, Down syndrome)
Trial locations and contacts
1 site in 1 country.
China1 site
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong
Haotian Lin, M.D., Ph.D, +86 13802793086, linht5@mail.sysu.edu
About this study
Official title: Impact of Feedback Based on the Myopia Prediction System on High Myopia Risk and Consultation Behavior in School-aged Children: a Cluster Randomized Controlled Trial
The global rise in myopia, particularly among children and adolescents in China, underscores the inadequacy of current prevention strategies, indicating that conventional screening and education alone are insufficient to curb the prevalence. Integrating personalized myopia prediction into routine care may enhance risk awareness, promote proactive prevention, and improve adherence to medical advice, ultimately reducing the future burden of high myopia.
A myopia prediction system based on artificial intelligence was previously developed, accurately predicting future high myopia risk using efficient, robust, and easily accessible predictive factors, including age, spherical equivalent, and the annual progression of spherical equivalent. This study aims to conduct a prospective, one-year, cluster randomized controlled clinical trial to investigate the effectiveness of this prediction system in preventing and controlling myopia in school-aged children.
- Being tested
- Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System, Feedback on Ophthalmic Examinations
- Keywords
- Myopia Prediction, Randomized Controlled Trials, Artificial Intelligence (AI)
- Medical subject headings
- Myopia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction SystemOther
At baseline and six months, participants will be provided with the results of their predicted risk of high myopia at age 18 based on the myopia prediction system.
Feedback on Ophthalmic ExaminationsOther
At baseline and six months, participants will be provided with the results of their ophthalmic examinations.
| Study group | Role | What they receive |
|---|---|---|
| Experimental Arm | Experimental | At baseline and six months, feedback on ophthalmic examination results and future high myopia risk at 18 years of age using the myopia prediction system Receives: Other: Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System; Other: Feedback on Ophthalmic Examinations |
| Control Arm | Active comparator | At baseline and six months, feedback on ophthalmic examination results. Receives: Other: Feedback on Ophthalmic Examinations |
What is being measured
The primary outcome is the main question the study is designed to answer.
Proportion of Individuals Predicted to Develop High Myopia at Age 18 by the Myopia Prediction System
At the end of the one-year study, the Myopia Prediction System will be used to predict whether students will develop high myopia at age 18 in both the intervention and control groups. The Proportion of Individuals Predicted to Develop High Myopia at Age 18 by the Myopia Prediction System is calculated as the total number of students in each group predicted to develop high myopia by age 18, divided by the total number of students in the respective group.
Measured: 1 year
Cumulative Clinical Visit Rate for Myopia Prevention and Control
The Cumulative Clinical Visit Rate Proportion of Clinical Visits for Myopia Prevention and Control is the proportion of students in the intervention or control group who visited a hospital or clinic for myopia-related care (e.g., refractive exams and treatment) at least once within three months of either intervention. It is calculated as the number of students in each group who attended a clinical visit within three months of at least one intervention, divided by the total number of students in the respective group.
Measured: Within 3 months after each intervention
Secondary outcomes (4)
Myopia Incidence Rate
1-year myopia incidence rate = number of new myopia cases within one year / number of non-myopic cases at baseline * 100%
Measured: 1 year
Changes in Spherical Equivalent
Change in spherical equivalent (non-cycloplegic autorefraction) will be calculated
Measured: 1 year
Screen Time
Daily usage time of electronic devices (computer/smartphone/tablet computer) will be calculated
Measured: 1 year
Outdoor Activity Time
Daily outdoor activity time will be calculated
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Oct 2024
- Study start1 Nov 2024 (estimated)
- Primary completion31 Dec 2025 (estimated)
- Study completion28 Feb 2026 (estimated)
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 MyopiaStudies of the same condition, open and under way.
- More trials run by Zhongshan Ophthalmic Center, 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 20,000 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Haotian Lin, Zhongshan Ophthalmic Center, Sun Yat-sen University
- Investigators
- Haotian Lin, M.D., Ph.D, Principal investigator, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06633393
- Sponsor's protocol ID
- 2024KYPJ102
- Status last verified
- Sep 2024
- First submitted
- 8 Oct 2024
- Last updated
- 15 Oct 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Lin H, Long E, Ding X, Diao H, Chen Z, Liu R, Huang J, Cai J, Xu S, Zhang X, Wang D, Chen K, Yu T, Wu D, Zhao X, Liu Z, Wu X, Jiang Y, Yang X, Cui D, Liu W, Zheng Y, Luo L, Wang H, Chan CC, Morgan IG, He M, Liu Y. Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study. PLoS Med. 2018 Nov 6;15(11):e1002674. doi: 10.1371/journal.pmed.1002674. eCollection 2018 Nov.
PubMed 30399150
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Impact of Feedback Based on the Myopia Prediction System on High Myopia Risk and Consultation Behavior in School-aged Children: a Cluster Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT06633393
- Acronym / sponsor ID
- 2024KYPJ102
- Keywords
- Myopia Prediction, Randomized Controlled Trials, Artificial Intelligence (AI)
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 20,000 participants (estimated)
- Lead sponsor
- Zhongshan Ophthalmic Center, Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 1 Nov 2024 (estimated)
- Primary completion
- 31 Dec 2025 (estimated)
- Study completion
- 28 Feb 2026 (estimated)
- First posted
- 9 Oct 2024 (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.
The global rise in myopia, particularly among children and adolescents in China, underscores the inadequacy of current prevention strategies, indicating that conventional screening and education alone are insufficient to curb the prevalence. Integrating personalized myopia prediction into routine care may enhance risk awareness, promote proactive prevention, and improve adherence to medical advice, ultimately reducing the future burden of high myopia.
A myopia prediction system based on artificial intelligence was previously developed, accurately predicting future high myopia risk using efficient, robust, and easily accessible predictive factors, including age, spherical equivalent, and the annual progression of spherical equivalent. This study aims to conduct a prospective, one-year, cluster randomized controlled clinical trial to investigate the effectiveness of this prediction system in preventing and controlling myopia in school-aged children.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Experimental Arm | Experimental | Other: Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System, Other: Feedback on Ophthalmic ExaminationsAt baseline and six months, feedback on ophthalmic examination results and future high myopia risk at 18 years of age using the myopia prediction system |
| Control Arm | Active comparator | Other: Feedback on Ophthalmic ExaminationsAt baseline and six months, feedback on ophthalmic examination results. |
Who may qualify
- Ages
- 9 to 11 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child
Key inclusion criteria (3 listed)
- The participant and their guardian voluntarily signed the informed consent form
- Has the record of eye refraction examination in the past year
- Aged 9 to 11 years, regardless of gender
Key exclusion criteria (3 listed)
- High myopia(spherical equivalent ≤ -6.00 D)
- Ocular diseases other than myopia (e.g., strabismus, amblyopia, congenital cataract, juvenile glaucoma, retinal diseases).
- Systemic diseases that may affect vision or visual development (e.g., diabetes or other endocrine disorders, cardiovascular or respiratory diseases, Down syndrome)
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 |
|---|---|---|
| Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction SystemAt baseline and six months, participants will be provided with the results of their predicted risk of high myopia at age 18 based on the myopia prediction system. | Other | Experimental Arm |
| Feedback on Ophthalmic ExaminationsAt baseline and six months, participants will be provided with the results of their ophthalmic examinations. | Other | Control Arm, Experimental Arm |
Primary outcome
Proportion of Individuals Predicted to Develop High Myopia at Age 18 by the Myopia Prediction System
Time frame: 1 year
At the end of the one-year study, the Myopia Prediction System will be used to predict whether students will develop high myopia at age 18 in both the intervention and control groups. The Proportion of Individuals Predicted to Develop High Myopia at Age 18 by the Myopia Prediction System is calculated as the total number of students in each group predicted to develop high myopia by age 18, divided by the total number of students in the respective group.
Cumulative Clinical Visit Rate for Myopia Prevention and Control
Time frame: Within 3 months after each intervention
The Cumulative Clinical Visit Rate Proportion of Clinical Visits for Myopia Prevention and Control is the proportion of students in the intervention or control group who visited a hospital or clinic for myopia-related care (e.g., refractive exams and treatment) at least once within three months of either intervention. It is calculated as the number of students in each group who attended a clinical visit within three months of at least one intervention, divided by the total number of students in the respective group.
4 secondary outcomes
Myopia Incidence Rate
Time frame: 1 year
Changes in Spherical Equivalent
Time frame: 1 year
Screen Time
Time frame: 1 year
Outdoor Activity Time
Time frame: 1 year
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2024.
- Background: PubMed 30399150Lin H, Long E, Ding X, Diao H, Chen Z, Liu R, Huang J, Cai J, Xu S, Zhang X, Wang D, Chen K, Yu T, Wu D, Zhao X, Liu Z, Wu X, Jiang Y, Yang X, Cui D, Liu W, Zheng Y, Luo L, Wang H, Chan CC, Morgan IG, He M, Liu Y. Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study. PLoS Med. 2018 Nov 6;15(11):e1002674. doi: 10.1371/journal.pmed.1002674. eCollection 2018 Nov.
- Individual participant dataSharing planned: No
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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.
Haotian Lin, M.D., Ph.D principal investigator
Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System and Feedback on Ophthalmic Examinations in people with Myopia and Randomized Controlled Trials, run by Zhongshan Ophthalmic Center, 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 3 inclusion and 3 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: status not confirmed, as of the sponsor's last update on 15 Oct 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Yahan Yang, M.D., Ph.D (+86 15521013933, yah.yang39@qq.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Proportion of Individuals Predicted to Develop High Myopia at Age 18 by the Myopia Prediction System (time frame: 1 year). The study lists 2 primary outcomes in all. 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 NCT06633393, 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 15 Oct 2024.