Influence of age and race on axial elongation in myopic children: A systematic review and meta-regression

Author:

Brennan Noel A.,Shamp Wright1,Maynes Elizabeth2,Cheng Xu1,Bullimore Mark A.3

Affiliation:

1. Johnson & Johnson, Jacksonville, Florida

2. Kelly Services, Inc., Troy, Michigan

3. College of Optometry, University of Houston, Houston, Texas

Abstract

PURPOSE Axial elongation is the basis of progression in primary myopia and the preferred metric to monitor its evolution. We conducted a meta-regression to model axial elongation and its associated factors in children with low to moderate myopia. METHODS A comprehensive electronic systematic search was performed using Ovid Medline, EMBASE, and Cochrane Central Register of Controlled Trials of studies conducted up until October 2021. The mean rate of axial elongation was analyzed using a multivariate linear mixed-effects meta-regression model, with backward stepwise elimination of nonsignificant covariates. The model included three levels of random effects, allowing both prediction and confidence intervals to be estimated. RESULTS A total of 64 studies with 83 subpopulations and 142 evaluations of mean axial change from baseline met our inclusion criteria and had no missing significant covariates in the final model. A separate analysis including all populations with axial length data (202 evaluations) but missing variance or covariate data produced a similar model to that for the analysis with complete data. The mean axial elongation is 38% greater in Asian children (95% confidence interval, 19 to 61%; p<0.01) compared with non-Asians, but both groups show a 15% decline per year as age increases (95% confidence interval, 12 to 17% p<0.0001). Prediction intervals indicate substantial variability around the axial elongation estimates. CONCLUSIONS This analysis provides mean values of axial elongation for evaluation of efficacy of myopia control. The broad prediction intervals emphasize the large range of individual axial elongation rates in the population, illustrating the challenge in managing individual children. Interpretation of the analysis is limited by the use of aggregated data rather than individual subject data.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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