Evidence map›Paper›PMID 42062967›Full record

ArticleBMC public health2026

Early identification of myopia risk in children through school-based vision screening: a longitudinal cohort study.

Luoming Huang, Yinhe Chen, Xueli Lin, Lei Huang, Xiwen Lan, Binni Wu, Yangyang Du

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Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Luoming HuangDepartment of Ophthalmology and Optometry, The School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, Fujian Province, 350000, China.ORCID 0000-0002-8348-9176
Yinhe ChenDepartment of Ophthalmology, Quanzhou Maternity and Children's Hospital, Quanzhou, Fujian Province, 362000, China. ysgcyh@163.com.
Xueli LinQuanzhou No.2 Experimental Primary School (Quanzhou Economic & Technological Development Zone Campus), Quanzhou, Fujian Province, China.
Lei HuangDepartment of Ophthalmology, Quanzhou Maternity and Children's Hospital, Quanzhou, Fujian Province, 362000, China.
Xiwen LanDepartment of Ophthalmology, Quanzhou Maternity and Children's Hospital, Quanzhou, Fujian Province, 362000, China.
Binni WuDepartment of Ophthalmology, Quanzhou Maternity and Children's Hospital, Quanzhou, Fujian Province, 362000, China.
Yangyang DuDepartment of Ophthalmology, Quanzhou Maternity and Children's Hospital, Quanzhou, Fujian Province, 362000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo develop and validate a myopia onset prediction model and a simplified scoring tool for school-aged children using longitudinal data from a routine school‑based vision screening program, based on parameters obtainable on‑site.

methodsThis retrospective longitudinal cohort study included data from a school‑based vision screening program conducted between 2021 and 2025, which measured non‑cycloplegic spherical equivalent (SE) and axial length (AL). A total of 3,749 children with complete baseline measurements were included. Among them, 1,969 children who were non‑myopic at baseline formed the prediction model development cohort. A multivariable logistic regression model was developed using baseline SE, AL, age, and gender, with myopia onset as the outcome. The model was trained on data from 2021 to 2023 and temporally validated on an independent cohort from 2024. A simplified risk scoring system was then derived from the regression coefficients.

resultsOver a minimum follow‑up of 0.5 years (0.97 ± 0.69 years), the model achieved AUCs of 0.795 (training) and 0.754 (validation). The simplified scoring system showed moderate discrimination (AUC = 0.739). Risk stratification into low‑, medium‑, and high‑risk groups yielded significantly different myopia‑free survival (p < 0.001), with cumulative incidences of 8.7%, 25.8%, and 87.3%, respectively. Decision curve analysis indicated net clinical benefit when using the model to guide interventions.

conclusionThe prediction model and simplified scoring tool, based on non‑cycloplegic refraction and AL, may help stratify children into myopic risk categories for targeted prevention in school and primary care settings. Further calibration improvement is needed before widespread implementation.

Indexed as

MyopiaSchool Health ServicesVision ScreeningChildEarly DiagnosisFemaleHumansLongitudinal StudiesMaleRetrospective StudiesRisk AssessmentAxial lengthMyopia predictionRisk stratificationVision screening

Identifiers

PMID42062967
PMCPMC13281565

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.