Paper Title: Influence of Age and Race on Axial Elongation in Myopic Children
Authors: Wright Shamp (1), Noel Brennan (1), Mark Bullimore (1), Xu Cheng (1), Elizabeth Maynes (1)
- Johnson & Johnson Vision
Date: May 2022
Reference: ARVO Meeting 2022, Denver [Link to conference abstract]
Percentile growth curves have been previously presented in research, specific to the age, sex and ethnicity of a particular population. These growth curves characterize typical myopia progression - children who are not undergoing myopia control treatment, such as single vision wearing children in control groups of myopia intervention studies.
This meta-analysis aimed to combine and explore all available data to test the variables of age and ethnicity for their contribution to axial length growth per year.
The meta-analysis included 79 studies with 105 untreated subpopulations. Evaluations of the change in axial length from baseline was included for 118 data sets, which included information on age and ethnicity.
The results showed that both age and ethnicity contributed to differences in mean axial length. Increasing age resulted in decreasing axial elongation per year, with a 15% decrease in mm/year per year of age. There was significant overlap between Asian and non-Asian children, but Asian children showed 28% greater annual axial elongation for their age compared to non-Asians. The baseline axial length of the child did not influence the rate of growth per year.
What does this mean for my practice?
Axial length growth curves denote the mean axial growth (mm/year) in children who are wearing single vision corrections (eg. untreated), and to date have been presented as distinct charts based on a child's age, sex and ethnicity. They can be used in practice to compare a child's axial growth to the average (the 50th percentile) and to determine the impact of myopia control treatments on continued eye growth.
Percentile growth charts are familiar to parents, used in other measures of childhood health such as height and weight. While age is the typical variable in growth charts (eg. the x-axis of the chart), interestingly, general childhood health growth charts produced by the World Health Organization do not differentiate by ethnicity, stating that they are applicable to all children "under optimal environmental conditions". It follows, then, to ask if separate ethnicity growth charts are needed for axial length.
This research appears to answer 'yes' - there is a significant increase in myopic eye growth for Asian compared to non-Asian children. Hence, we're likely to continue to need different percentile charts for children based on their ethnicity.
What do we still need to learn?
At the moment, percentile growth charts for axial length are available for specific populations based on geography (East Asia vs Europe) and ethnicity (Asian vs non-Asian). We're yet to understand how ethnicity may interact with location to influence axial length growth. There may be an impact, as there is for myopia prevalence - for example, children of Chinese ethnicity have been shown to exhibit different rates of myopia based on country of residence.
Title: Influence of Age and Race on Axial Elongation in Myopic Children
Authors:Wright Shamp, Noel Brennan, Mark Bullimore, Xu Cheng, Elizabeth Maynes
Purpose: With increasing emphasis on slowing myopia progression and using axial length to monitor eye growth, normative data for axial elongation in myopic children provide valuable clinical information. Percentile growth curves have been presented but are specific to the population tested and often include myopes and non-myopes, limiting their application. We conducted a meta-analysis to model axial elongation in myopic children with emphasis on the influence of age and race.
Methods: A comprehensive electronic systematic search was performed using Ovid Medline, EMBASE, Cochrane Central Register of Controlled Trials and the following terms: (myopia OR myopic) AND (child OR children) AND (progression OR longitudinal OR follow-up OR shift) AND axial. There were 79 studies with 105 untreated subpopulations and 203 evaluations of the mean axial change from baseline that met the inclusion criteria. Log(mean rate of axial elongation) was analyzed using a weighted multivariable linear mixed effects meta-analysis model. All collected covariates were tested for significance (age, race and baseline axial length selected). The model included three levels of random effects to account for all variability.
Results: Only data without missing observations of significant covariates were included in the final model (118 evaluations). The figure plots modeled annual axial elongation (with prediction intervals) by mean age of evaluation and race. Mean axial elongation decreases as age increases (15.0% decrease per year; 95%CI 11.4–18.5%, P <0.0001) and is greater in Asian children (by 27.9%; 95%CI 7.6–52.2%, P <0.01) compared to non-Asians. No other input variables, including baseline axial length, were statistically significant.
Conclusions: This analysis sets benchmark values for assessing axial elongation and monitoring myopia progression. To our knowledge, this is the first weighted random effects meta-analysis of axial elongation in myopic children. Interpretation is limited by use of aggregated data rather than individual subject data. The large prediction intervals should be borne in mind when interpreting individual rates of axial elongation clinically.