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Updated: Sep 9, 2025
Inducement and Evaluation of a Murine Model of Experimental Myopia
Published on: January 22, 2019
A nomogram for identifying premyopia and myopia candidates in Chinese children: focusing on those with cycloplegic
Jing Wu1, Cong Zhang2, Jingying Wang3
1Ophthalmology Department, The University of Hong Kong-Shenzhen Hospital, ShenZhen, Guangdong, China.
Insights
This study developed a nomogram using primary refractive error screening parameters to identify children at risk for myopia. This tool aids in early detection and intervention for premyopia and myopia prevention.
Area of Science:
- Ophthalmology
- Pediatric Optometry
- Public Health
Background:
- Routine refractive error screening is crucial for myopia management.
- Current methods for identifying premyopia and myopia intervention candidates require further refinement.
- Early detection of myopia risk factors is essential for timely intervention.
Purpose of the Study:
- To develop a predictive nomogram for identifying premyopia and myopia intervention candidates.
- To utilize routinely measured refractive error parameters for myopia prediction.
- To support clinical decision-making in premyopia and myopia prevention strategies.
Main Methods:
- A retrospective cohort study of pediatric patients (aged 4-17) in China.
- Logistic regression with multiple imputations was used to build a predictive model.
- Key parameters included age, gender, uncorrected visual acuity (UCVA), axial length (AL), and others.
Main Results:
- The nomogram incorporated UCVA, non-cycloplegic spherical equivalent refraction (NCSER), AL, and AL/ACRC ratio as independent predictors.
- The nomogram demonstrated high predictive accuracy with an AUC of 0.971 in the derivation set and 0.921 in the external validation set.
- Calibration and decision curve analysis confirmed the nomogram's robust clinical utility.
Conclusions:
- A nomogram based on primary refractive error screening parameters can effectively predict premyopia and myopia intervention candidates.
- This tool has the potential to enhance clinical decision-making for myopia prevention.
- Further application of this nomogram can facilitate early intervention strategies for childhood myopia.
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.
