A nomogram for identifying premyopia and myopia candidates in Chinese children: focusing on those with cycloplegic spherical equivalent refraction ≤ + 0.75D.

Abstract

Background: Primary refractive error screening parameters are commonly employed in clinical and community settings before cycloplegic assessment of myopia, however, their utility in identifying premyopia and myopia intervention candidates remains underexplored. This study aimed to develop a nomogram based on these routinely measured parameters to support clinical decision-making for premyopia and myopia prevention.

Methods: Pediatric patients (aged 4-17 years) from two medical centers in China were enrolled in this retrospective cohort study. A predictive model for the candidates of premyopia and myopia intervention was developed using logistic regression with multiple imputations. The model included the following primary screening parameters: age, gender, uncorrected visual acuity (UCVA), average corneal curvature (ACC), non-cycloplegic spherical equivalent refraction (NCSER), axial length (AL), and the axial length to average corneal radius of curvature (AL/ACRC) ratio. The efficacy of the model was assessed using the area under the receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA). R was employed to conduct all statistical analyses.

Results: A total of 1006 participants (507 females, 499 boys) were enrolled, with 87.4% demonstrating cycloplegic spherical equivalent refraction (CSER) ≤ + 0.75D. In multivariate logistic regression, UCVA, NCSER, AL, and AL/ACRC were identified as independent predictors. These predictors were incorporated into a nomogram to predict the candidates for premyopia and myopia intervention. The nomogram exhibited exceptional discrimination in the derivation set (AUC = 0.971, 95% CI: 0.957-0.984), whereas in the external validation set, the AUC was 0.921 (95% CI: 0.866-0.976) when a cutoff of 0.851 in derivation set was employed. Calibration was verified through the calibration curve and Hosmer-Lemeshow tests (P = 0.99 and P = 0.96, respectively), and the decision curve analysis demonstrated robust clinical utility for threshold probabilities of 0.10-1.00 in the derivation set and 0.20-1.00 in the external validation set.

Conclusion: The nomogram derived from the parameters of primary refractive error screening has the potential to preliminarily predict premyopia and myopia intervention candidates, thereby facilitating clinical decision-making in the context of premyopia and myopia prevention.