Key Takeaways

  • A prediction model developed from 4 years of school vision screening data successfully identified children at increased risk of developing myopia before disease onset
  • Temporal validation in an independent cohort demonstrated good predictive performance despite differences in baseline characteristics and myopia incidence
  • At a 10% risk threshold, the model could reduce unnecessary preventive interventions by nearly half compared with treating all children while maintaining identification of those at highest risk

A prediction model developed using data from a routine school vision screening program could help identify children at elevated risk of developing myopia before disease onset. The research may enable clinicians and public health programs to target preventive interventions more efficiently, according to a study published in BMC Public Health.1

The investigators developed and temporally validated the model using 4 years of longitudinal data collected from school-aged children. Unlike many prediction studies that rely solely on internal validation, the researchers evaluated the model in an independent cohort with substantially different baseline characteristics and a higher incidence of myopia, demonstrating that its predictive performance remained robust across populations.

The authors said the model was designed to support early identification of children who are most likely to develop myopia, an approach that could improve the efficiency of preventive strategies as myopia prevalence continues to rise worldwide.

Decision curve analysis suggested that using the model to guide intervention decisions offered greater clinical benefit than either intervening in all children or withholding intervention altogether across clinically relevant risk thresholds ranging from 5% to 20%.

At a 10% predicted-risk threshold, the researchers estimated that applying the model to a cohort of 1,660 children would avoid approximately 667 unnecessary preventive interventions compared with a universal treatment approach. This represented a 49.3% reduction in false-positive interventions while maintaining identification of children most likely to develop myopia.

Although the study did not evaluate specific myopia control therapies, the findings have implications for increasingly common interventions such as low-dose atropine, orthokeratology, multifocal contact lenses and behavioral strategies aimed at increasing outdoor time. A validated risk stratification tool could help clinicians determine which children may benefit most from closer monitoring or earlier preventive management, the researchers said.

The investigators noted that the model was developed using data generated through routine school vision screening, highlighting its potential applicability in community-based screening programs. Because the validation cohort differed substantially from the development cohort, the authors suggested the findings support the model's generalizability, although additional validation in other geographic regions and healthcare settings would further establish its clinical utility.

Reference

Huang L, Chen Y, Lin X, et al. Early identification of myopia risk in children through school-based vision screening: a longitudinal cohort study. BMC Public Health. 2026;26:1919. doi:10.1186/s12889-026-27431-z.