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Published on: March 29, 2022
Myopia progression patterns among paediatric patients in a clinical setting
Michael Moore1, Gareth Lingham1,2, Daniel I Flitcroft1,3
1Centre for Eye Research Ireland, School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Dublin, Ireland.
Insights
This study analyzed untreated myopia progression in children aged 7-17. Progression was fastest in younger children and slowed with age, informing future myopia management strategies.
Area of Science:
- Ophthalmology
- Pediatric Optometry
- Myopia Research
Background:
- Myopic progression in children is a growing concern globally.
- Understanding the natural history of untreated myopia is crucial for effective management.
- Existing data on myopia progression rates in children often lack real-world, diverse patient populations.
Purpose of the Study:
- To investigate the natural history of myopic progression in children using electronic medical record (EMR) data from Irish optometric practices.
- To establish age- and sex-specific population centiles for annual myopic progression in untreated children.
- To compare observed progression rates with data from randomized clinical trials (RCTs) and predictive models.
Main Methods:
- Retrospective analysis of EMR data from myopic patients aged 7-17 without myopia control treatment.
- Derivation of population centiles for annual myopic progression using weighted cubic splines.
- Comparison with RCT control group data and analysis using linear mixed models (LMMs) and survival analysis.
Main Results:
- Myopia progression was highest at age 7 (median: -0.67 D/year) and slowed with age (median: -0.18 D/year at age 17).
- Faster progression was predicted by female sex, higher baseline myopia, and younger age.
- RCT control groups showed higher mean progression than observed EMR data; clinic-based studies aligned more closely.
Conclusions:
- The study provides valuable progression centiles for untreated myopic children, defining the natural history of myopia.
- These findings will aid clinicians in predicting refractive outcomes without treatment.
- The data will also support monitoring treatment efficacy, especially when axial length data is unavailable.
Purpose:
This retrospective analysis of electronic medical record (EMR) data investigated the natural history of myopic progression in children from optometric practices in Ireland.
Methods:
The analysis was of myopic patients aged 7-17 with multiple visits and not prescribed myopia control treatment. Sex- and age-specific population centiles for annual myopic progression were derived by fitting a weighted cubic spline to empirical quantiles. These were compared to progression rates derived from control group data obtained from 17 randomised clinical trials (RCTs) for myopia. Linear mixed models (LMMs) were used to allow comparison of myopia progression rates against outputs from a predictive online calculator. Survival analysis was performed to determine the intervals at which a significant level of myopic progression was predicted to occur.
Results:
Myopia progression was highest in children aged 7 years (median: -0.67 D/year) and progressively slowed with increasing age (median: -0.18 D/year at age 17). Female sex (p < 0.001), a more myopic SER at baseline (p < 0.001) and younger age (p < 0.001) were all found to be predictive of faster myopic progression. Every RCT exhibited a mean progression higher than the median centile observed in the EMR data, while clinic-based studies more closely matched the median progression rates. The LMM predicted faster myopia progression for patients with higher baseline myopia levels, in keeping with previous studies, which was in contrast to an online calculator that predicted slower myopia progression for patients with higher baseline myopia. Survival analysis indicated that at a recall period of 12 months, myopia will have progressed in between 10% and 70% of children, depending upon age.
Conclusions:
This study produced progression centiles of untreated myopic children, helping to define the natural history of untreated myopia. This will enable clinicians to better predict both refractive outcomes without treatment and monitor treatment efficacy, particularly in the absence of axial length data.
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