Development of a concise objective biometric triage model for identifying myopia defined by cycloplegic refraction in school-aged children

To develop a concise objective biometric triage model using non-cycloplegic ocular biometric parameters to identify school-aged children likely to have myopia defined by cycloplegic spherical equivalent (SE ≤ − 0.50 D). In this study, 2,851 children aged 6–10 years from Wuchang and Jiang’an Districts of Wuhan, China, were included. To avoid inter-eye correlation, only right-eye data were analyzed. Myopia was defined as cycloplegic SE ≤ − 0.50 D. Three objective non-cycloplegic predictors, age, sex, and axial length-to-corneal radius ratio (AL/CR), were entered into a logistic regression model. The dataset was randomly divided into training and validation sets at an 8:2 ratio. Model discrimination, calibration, and clinical utility were assessed using receiver operating characteristic analysis, calibration curve, decision curve analysis, and reclassification statistics. The combined model (age, sex, AL/CR) demonstrated high discriminative performance (AUC = 0.941, 95% CI: 0.921–0.960), significantly outperforming both the AL/CR-only model (AUC = 0.935) and the demographic baseline model (AUC = 0.655) (DeLong test, P < 0.001). At the default threshold, the model exhibited high specificity (97.99%) and precision (88.16%) but limited sensitivity (54.03%). Calibration was acceptable (Brier score = 0.102), and decision curve analysis indicated potential net benefit. The optimal AL/CR cutoff of 3.02 from the univariable analysis is presented merely as an unadjusted descriptive reference, as the combined model provides individualized risk estimation across all subgroups. A concise model based on age, sex, and AL/CR showed good discrimination for identifying myopia defined by cycloplegic refraction. However, because the model showed limited sensitivity at the default operating threshold, it should be considered an adjunctive biometric triage tool rather than a stand-alone replacement for established screening methods or confirmatory cycloplegic refraction. Further studies with direct comparison against non-cycloplegic autorefraction and UDVA-based screening strategies are warranted.

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Publication Details

Journal
Scientific Reports
Published
2026-10-26
DOI
https://doi.org/10.1038/s41598-026-53168-1
Primary Topic
Ophthalmology and Visual Impairment Studies
Type
article
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article

Development of a concise objective biometric triage model for identifying myopia defined by cycloplegic refraction in school-aged children

Xiang Wan, Ruihua Wei, Zixun Wang, Yin Li et al.
Scientific Reports
Ophthalmology and Visual Impairment Studies
article

Development of a concise objective biometric triage model for identifying myopia defined by cycloplegic refraction in school-aged children

Xiang Wan, Ruihua Wei, Zixun Wang, Yin Li, Boxuan Sun, Feng Chang, Xiaoxue Hu
article en

Abstract

To develop a concise objective biometric triage model using non-cycloplegic ocular biometric parameters to identify school-aged children likely to have myopia defined by cycloplegic spherical equivalent (SE ≤ − 0.50 D). In this study, 2,851 children aged 6–10 years from Wuchang and Jiang’an Districts of Wuhan, China, were included. To avoid inter-eye correlation, only right-eye data were analyzed. Myopia was defined as cycloplegic SE ≤ − 0.50 D. Three objective non-cycloplegic predictors, age, sex, and axial length-to-corneal radius ratio (AL/CR), were entered into a logistic regression model. The dataset was randomly divided into training and validation sets at an 8:2 ratio. Model discrimination, calibration, and clinical utility were assessed using receiver operating characteristic analysis, calibration curve, decision curve analysis, and reclassification statistics. The combined model (age, sex, AL/CR) demonstrated high discriminative performance (AUC = 0.941, 95% CI: 0.921–0.960), significantly outperforming both the AL/CR-only model (AUC = 0.935) and the demographic baseline model (AUC = 0.655) (DeLong test, P < 0.001). At the default threshold, the model exhibited high specificity (97.99%) and precision (88.16%) but limited sensitivity (54.03%). Calibration was acceptable (Brier score = 0.102), and decision curve analysis indicated potential net benefit. The optimal AL/CR cutoff of 3.02 from the univariable analysis is presented merely as an unadjusted descriptive reference, as the combined model provides individualized risk estimation across all subgroups. A concise model based on age, sex, and AL/CR showed good discrimination for identifying myopia defined by cycloplegic refraction. However, because the model showed limited sensitivity at the default operating threshold, it should be considered an adjunctive biometric triage tool rather than a stand-alone replacement for established screening methods or confirmatory cycloplegic refraction. Further studies with direct comparison against non-cycloplegic autorefraction and UDVA-based screening strategies are warranted.

Scientific Reports
Tianjin University (CN), Wuhan Children's Hospital (CN), Central Hospital of Wuhan (CN), Tianjin Medical University Eye Hospital (CN), Huazhong University of Science and Technology (CN), Tianjin Medical University (CN)
Openalex Percentile: Top 12%
Ophthalmology and Visual Impairment Studies
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