Validation of a Predictive Algorithm to Determine the Effectiveness of Orthokeratology for Myopia Control

Study Overview
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Brief Summary
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This is a prospective study to validate a predictive algorithm for identifying fast progressing myopes.

Detailed Description
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Orthokeratology (ortho-K) has been demonstrated to slow myopic progression and reduce axial elongation in young patients, but this treatment is limited by the need for contact lens wear, which is the common cause for keratitis in children, and therefore cautious use is recommended. There is a need to identify the patients that could benefit most from this treatment. In order to do so, we conduct a retrospective study and create a large database (n = 10,000) of de-identified data to train an algorithm for identifying fast progressing myopes. In addition, we will perform a prospective study to validate this predictive algorithm and determine the effectiveness of Orthokeratology among different individual patients in China.

Official Title
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Validation of a Predictive Algorithm to Determine the Effectiveness of Orthokeratology for Myopia Control

Conditions
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Myopia

Intervention / Treatment
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* Device: Orthokeratology lenses


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: -6.0D≤SER≤-0.5D Astigmatism≤2.0D Exclusion Criteria: Contraindications of wearing Ortho-K. Diagnosis of strabismus, amblyopia and other refractive development of the eye or systemic diseases. Currently involved in other clinical studies.

Ages Eligible for Study
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Minimum Age: 8 Years
Maximum Age: 15 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Children with myopia<br>A total of 3,000 children from Zhongshan Ophthalmic Center is required to undergo ophthalmic examinations and complete questionnaires at baseline and 1yr after wearing Ortho-K. | Device: Orthokeratology lenses<br>* Orthokeratology lenses<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| AUROC of the prediction algorithm for identifying fast progressing myopes | Age-specific axial length (AL) changes previously described by Wang et al.(IOVS, 52 (11), 7949-53, 2011) are used as cut-off values to determine whether a child is a fast progressor or not. A child whose AL change falls on or above the cut-off value is considered to be a fast progressor. | 1 year | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sensitivity and specificity of the prediction algorithm for identifying fast progressing myopes | The investigators will estimate sensitivity and specificity of the predictive algorithm for identifying fast progressing myopes. | 1 year | 
| Performance of an algorithm for predicting AL | The investigators will use mean absolute error (MAE), R square to evaluate the performance. | 1 year | 
| Performance of an algorithm for predicting spherical equivalent refractive error | The investigators will use mean absolute error (MAE), R square to evaluate the performance. | 1 year |