The growing problem of myopia: improving prediction of onset and progression

Abstract

Introduction:
Evidence is accumulating to support prophylactic measures to delay onset and progression of myopia. To enact these measures, robust prediction strategies are required to identify children at risk of developing myopia (pre-myopes) and those at risk of fast myopia progression.

Aims and methods:
This thesis explored five key areas in pursuit of useful methods to predict myopia onset and progression. The identification of pre-myopic children was explored through evaluation and validation of the PreMO risk indicator when applied to prospective paediatric cohorts from the UK and Hong Kong. Melatonin, relative peripheral refraction (RPR) and sub-foveal choroidal thickness (SFCT) were investigated to determine their potential as predictive factors for myopia. Methods included a cross-sectional study of morning salivary melatonin in myopic and non-myopic children, and an observational study of myopic children prescribed MiYOSMART myopia ‘control’ spectacle lenses. IOLMaster 700 scans were evaluated to determine their capability to provide useful estimates of SFCT.

Results:
PreMO scores ≥ 4 were highly sensitive and specific in predicting future myopia in UK and Hong Kong children. In established myopes wearing MiYOSMART lenses, a more hyperopic RPR and thicker SFCT at baseline were significantly associated with greater myopia ‘control’, as was an increase in SFCT over 6- or 12-months of MiYOSMART wear. Elevated melatonin levels previously identified in myopic adults were not detected in adolescent myopes. It was possible to identify ‘thick’ and ‘thin’ choroids from IOLMaster 700 scans.

Conclusions:
Clinicians can confidently use the PreMO risk indicator to identify pre-myopic children and instigate targeted advice and monitoring. Once myopia is established, RPR and SFCT measures are useful metrics for predicting success in myopia management. As these metrics are not currently part of standard clinical assessment, xviii future work should focus on the development of tools and algorithms to support clinicians in adopting them into routine practice.

Thesis is embargoed until 30 June 2026

Date of Award	Jun 2024
Original language	English
Supervisor	Patrick Richardson (Supervisor), Sara McCullough (Supervisor) & Kathryn Saunders (Supervisor)