Kristen L. Kerber

Purpose We used baseline data from the PICNIC longitudinal study to investigate structural, functional, behavioural and heritable metrics that may predict future myopia in young children. Methods Cycloplegic refractive error (M) and optical biometry were obtained in 97 young children with functional emmetropia. Children were classified as high risk (HR) or low risk (LR) for myopia based on parental myopia and M. Other metrics included axial length (AXL), axial length/corneal radius (AXL/CR) and refractive centile curves. Results Based on the PICNIC criteria, 46 children (26 female) were classified as HR (M = +0.62 ± 0.44 D, AXL = 22.80 ± 0.64 mm) and 51 (27 female) as LR (M = +1.26 ± 0.44 D, AXL = 22.77 ± 0.77 mm). Based on centiles, 49 children were HR, with moderate agreement compared with the PICNIC classification (k = 0.65, p < 0.01). ANCOVA with age as a covariate showed a significant effect for AXL ( p < 0.01), with longer AXL and deeper anterior chamber depth (ACD) ( p = 0.01) in those at HR (differences AXL = 0.16 mm, ACD = 0.13 mm). Linear regression models showed that central corneal thickness (CCT), ACD, posterior vitreous depth (PVD) (=AXL – CCT – ACD‐lens thickness (LT)), corneal radius (CR) and age significantly predicted M ( R = 0.64, p < 0.01). Each 1.00 D decrease in hyperopia was associated with a 0.97 mm elongation in PVD and 0.43 mm increase in CR. The ratio AXL/CR significantly predicted M ( R = −0.45, p < 0.01), as did AXL ( R = −0.25, p = 0.01), although to a lesser extent. Conclusions Although M and AXL were highly correlated, the classification of pre‐myopic children into HR or LR was significantly different when using each parameter, with AXL/CR being the most predictive metric. At the end of the longitudinal study, we will be able to assess the predictability of each metric.