Development and Validation of a Model to Predict Who Will Develop Myopia in the Following Year as a Criterion to Define Premyopia
To develop and validate models to predict who will develop myopia in the following year based on cycloplegic refraction or ocular biometry and to identify thresholds of premyopia. Prospective longitudinal data of nonmyopic children at baseline from the Guangzhou Twins Eye Study and the Guangzhou Out...
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Veröffentlicht in: | Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) Pa.), 2023-01, Vol.12 (1), p.38-43 |
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creator | Chen, Yanxian Tan, Cheng Foo, Li-Lian He, Siyan Zhang, Jian Bulloch, Gabriella Saw, Seang-Mei Li, Jinying Morgan, Ian Guo, Xiaobo He, Mingguang |
description | To develop and validate models to predict who will develop myopia in the following year based on cycloplegic refraction or ocular biometry and to identify thresholds of premyopia.
Prospective longitudinal data of nonmyopic children at baseline from the Guangzhou Twins Eye Study and the Guangzhou Outdoor Activity Longitudinal Study were used as the training set, and the Singapore Cohort Study of the Risk factors for Myopia study formed the external validation set. Age, sex, cycloplegic refraction, ocular biometry, uncorrected visual acuity, and parental myopia were integrated into 3 logistic regression models to predict the onset of myopia in the following year. Premyopia cutoffs and an integer risk score system were derived based on the identified risk.
In total, 2896 subjects with at least 2 visits were included. Cycloplegic refraction at baseline is a better predictor to identify the children with myopia onset [C-statistic=0.91, 95% confidence interval (CI), 0.87-0.94; C-statistic=0.92, 95% CI, 0.92-0.92 for internal and external validation, respectively], comparing to axial length, corneal curvature radius (CR) and anterior chamber depth (C-statistic=0.81, 95% CI, 0.73-0.88; C-statistic=0.80, 95% CI, 0.79-0.80, respectively), and axial length/CR (C-statistic=0.78, 95% CI, 0.71-0.85; C-statistic=0.76, 95% CI, 0.75-0.76). With a risk of >70%, the definitions of premyopia indicating approaching myopia onset were 0.00 D for 6-8 years and -0.25 D for ≥9 years in children with 2 myopic parents.
Either cycloplegic refraction or ocular biometry can predict 1-year risk of myopia. Premyopia can be successfully defined through risk assessments based on children's age and predict who would require more aggressive myopia prophylaxis. |
doi_str_mv | 10.1097/APO.0000000000000591 |
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Prospective longitudinal data of nonmyopic children at baseline from the Guangzhou Twins Eye Study and the Guangzhou Outdoor Activity Longitudinal Study were used as the training set, and the Singapore Cohort Study of the Risk factors for Myopia study formed the external validation set. Age, sex, cycloplegic refraction, ocular biometry, uncorrected visual acuity, and parental myopia were integrated into 3 logistic regression models to predict the onset of myopia in the following year. Premyopia cutoffs and an integer risk score system were derived based on the identified risk.
In total, 2896 subjects with at least 2 visits were included. Cycloplegic refraction at baseline is a better predictor to identify the children with myopia onset [C-statistic=0.91, 95% confidence interval (CI), 0.87-0.94; C-statistic=0.92, 95% CI, 0.92-0.92 for internal and external validation, respectively], comparing to axial length, corneal curvature radius (CR) and anterior chamber depth (C-statistic=0.81, 95% CI, 0.73-0.88; C-statistic=0.80, 95% CI, 0.79-0.80, respectively), and axial length/CR (C-statistic=0.78, 95% CI, 0.71-0.85; C-statistic=0.76, 95% CI, 0.75-0.76). With a risk of >70%, the definitions of premyopia indicating approaching myopia onset were 0.00 D for 6-8 years and -0.25 D for ≥9 years in children with 2 myopic parents.
Either cycloplegic refraction or ocular biometry can predict 1-year risk of myopia. Premyopia can be successfully defined through risk assessments based on children's age and predict who would require more aggressive myopia prophylaxis.</description><identifier>ISSN: 2162-0989</identifier><identifier>EISSN: 2162-0989</identifier><identifier>DOI: 10.1097/APO.0000000000000591</identifier><identifier>PMID: 36706333</identifier><language>eng</language><publisher>United States: Lippincott Williams & Wilkins</publisher><subject>Child ; Cohort Studies ; Humans ; Longitudinal Studies ; Mydriatics ; Myopia - diagnosis ; Prospective Studies ; Refraction, Ocular</subject><ispartof>Asia-Pacific journal of ophthalmology (Philadelphia, Pa.), 2023-01, Vol.12 (1), p.38-43</ispartof><rights>Lippincott Williams & Wilkins</rights><rights>Copyright © 2023 Asia-Pacific Academy of Ophthalmology. Published by Wolters Kluwer Health, Inc. on behalf of the Asia-Pacific Academy of Ophthalmology.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3986-2cc1f0dad992daff632f9c9e83186c330c796c9213f43b018474dfe9896f19a3</citedby><cites>FETCH-LOGICAL-c3986-2cc1f0dad992daff632f9c9e83186c330c796c9213f43b018474dfe9896f19a3</cites><orcidid>0000-0002-5721-6051</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36706333$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Yanxian</creatorcontrib><creatorcontrib>Tan, Cheng</creatorcontrib><creatorcontrib>Foo, Li-Lian</creatorcontrib><creatorcontrib>He, Siyan</creatorcontrib><creatorcontrib>Zhang, Jian</creatorcontrib><creatorcontrib>Bulloch, Gabriella</creatorcontrib><creatorcontrib>Saw, Seang-Mei</creatorcontrib><creatorcontrib>Li, Jinying</creatorcontrib><creatorcontrib>Morgan, Ian</creatorcontrib><creatorcontrib>Guo, Xiaobo</creatorcontrib><creatorcontrib>He, Mingguang</creatorcontrib><title>Development and Validation of a Model to Predict Who Will Develop Myopia in the Following Year as a Criterion to Define Premyopia</title><title>Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)</title><addtitle>Asia Pac J Ophthalmol (Phila)</addtitle><description>To develop and validate models to predict who will develop myopia in the following year based on cycloplegic refraction or ocular biometry and to identify thresholds of premyopia.
Prospective longitudinal data of nonmyopic children at baseline from the Guangzhou Twins Eye Study and the Guangzhou Outdoor Activity Longitudinal Study were used as the training set, and the Singapore Cohort Study of the Risk factors for Myopia study formed the external validation set. Age, sex, cycloplegic refraction, ocular biometry, uncorrected visual acuity, and parental myopia were integrated into 3 logistic regression models to predict the onset of myopia in the following year. Premyopia cutoffs and an integer risk score system were derived based on the identified risk.
In total, 2896 subjects with at least 2 visits were included. Cycloplegic refraction at baseline is a better predictor to identify the children with myopia onset [C-statistic=0.91, 95% confidence interval (CI), 0.87-0.94; C-statistic=0.92, 95% CI, 0.92-0.92 for internal and external validation, respectively], comparing to axial length, corneal curvature radius (CR) and anterior chamber depth (C-statistic=0.81, 95% CI, 0.73-0.88; C-statistic=0.80, 95% CI, 0.79-0.80, respectively), and axial length/CR (C-statistic=0.78, 95% CI, 0.71-0.85; C-statistic=0.76, 95% CI, 0.75-0.76). With a risk of >70%, the definitions of premyopia indicating approaching myopia onset were 0.00 D for 6-8 years and -0.25 D for ≥9 years in children with 2 myopic parents.
Either cycloplegic refraction or ocular biometry can predict 1-year risk of myopia. Premyopia can be successfully defined through risk assessments based on children's age and predict who would require more aggressive myopia prophylaxis.</description><subject>Child</subject><subject>Cohort Studies</subject><subject>Humans</subject><subject>Longitudinal Studies</subject><subject>Mydriatics</subject><subject>Myopia - diagnosis</subject><subject>Prospective Studies</subject><subject>Refraction, Ocular</subject><issn>2162-0989</issn><issn>2162-0989</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkUFPHCEYholpo8b6D4zh6GXsB8wyw9GstW2i0YOp6YkgfLi0zLDCbDce-8_L6tqacoHD-z5feD5CjhicMlDdx7Ob61N4e2aK7ZB9ziRvQPXq3Zv3Hjks5ccmJIEB73fJnpAdSCHEPvl9jr8wpuWA40TN6Og3E4MzU0gjTZ4aepUcRjolepPRBTvRu0WidyFGum3Sq6e0DIaGkU4LpBcpxrQO4wP9jiZTUypjnsOEeYOsnHP0YcQNbngufiDvvYkFD7f3Abm9-HQ7_9JcXn_-Oj-7bKxQvWy4tcyDM04p7oz3UnCvrMJesF5aIcB2SlrFmfCtuAfWt13rPNb_S8-UEQfk5AW7zOlxhWXSQygWYzQjplXRvOug7WHWiRptX6I2p1Iyer3MYTD5STPQG_266tf_66-14-2E1f2A7m_pVfY_7jrF6qP8jKs1Zr1AE6eFBjZTqo5vOHBRFwXQPO9M_AEVwI80</recordid><startdate>202301</startdate><enddate>202301</enddate><creator>Chen, Yanxian</creator><creator>Tan, Cheng</creator><creator>Foo, Li-Lian</creator><creator>He, Siyan</creator><creator>Zhang, Jian</creator><creator>Bulloch, Gabriella</creator><creator>Saw, Seang-Mei</creator><creator>Li, Jinying</creator><creator>Morgan, Ian</creator><creator>Guo, Xiaobo</creator><creator>He, Mingguang</creator><general>Lippincott Williams & Wilkins</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-5721-6051</orcidid></search><sort><creationdate>202301</creationdate><title>Development and Validation of a Model to Predict Who Will Develop Myopia in the Following Year as a Criterion to Define Premyopia</title><author>Chen, Yanxian ; Tan, Cheng ; Foo, Li-Lian ; He, Siyan ; Zhang, Jian ; Bulloch, Gabriella ; Saw, Seang-Mei ; Li, Jinying ; Morgan, Ian ; Guo, Xiaobo ; He, Mingguang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3986-2cc1f0dad992daff632f9c9e83186c330c796c9213f43b018474dfe9896f19a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Child</topic><topic>Cohort Studies</topic><topic>Humans</topic><topic>Longitudinal Studies</topic><topic>Mydriatics</topic><topic>Myopia - diagnosis</topic><topic>Prospective Studies</topic><topic>Refraction, Ocular</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Yanxian</creatorcontrib><creatorcontrib>Tan, Cheng</creatorcontrib><creatorcontrib>Foo, Li-Lian</creatorcontrib><creatorcontrib>He, Siyan</creatorcontrib><creatorcontrib>Zhang, Jian</creatorcontrib><creatorcontrib>Bulloch, Gabriella</creatorcontrib><creatorcontrib>Saw, Seang-Mei</creatorcontrib><creatorcontrib>Li, Jinying</creatorcontrib><creatorcontrib>Morgan, Ian</creatorcontrib><creatorcontrib>Guo, Xiaobo</creatorcontrib><creatorcontrib>He, Mingguang</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Yanxian</au><au>Tan, Cheng</au><au>Foo, Li-Lian</au><au>He, Siyan</au><au>Zhang, Jian</au><au>Bulloch, Gabriella</au><au>Saw, Seang-Mei</au><au>Li, Jinying</au><au>Morgan, Ian</au><au>Guo, Xiaobo</au><au>He, Mingguang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development and Validation of a Model to Predict Who Will Develop Myopia in the Following Year as a Criterion to Define Premyopia</atitle><jtitle>Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)</jtitle><addtitle>Asia Pac J Ophthalmol (Phila)</addtitle><date>2023-01</date><risdate>2023</risdate><volume>12</volume><issue>1</issue><spage>38</spage><epage>43</epage><pages>38-43</pages><issn>2162-0989</issn><eissn>2162-0989</eissn><abstract>To develop and validate models to predict who will develop myopia in the following year based on cycloplegic refraction or ocular biometry and to identify thresholds of premyopia.
Prospective longitudinal data of nonmyopic children at baseline from the Guangzhou Twins Eye Study and the Guangzhou Outdoor Activity Longitudinal Study were used as the training set, and the Singapore Cohort Study of the Risk factors for Myopia study formed the external validation set. Age, sex, cycloplegic refraction, ocular biometry, uncorrected visual acuity, and parental myopia were integrated into 3 logistic regression models to predict the onset of myopia in the following year. Premyopia cutoffs and an integer risk score system were derived based on the identified risk.
In total, 2896 subjects with at least 2 visits were included. Cycloplegic refraction at baseline is a better predictor to identify the children with myopia onset [C-statistic=0.91, 95% confidence interval (CI), 0.87-0.94; C-statistic=0.92, 95% CI, 0.92-0.92 for internal and external validation, respectively], comparing to axial length, corneal curvature radius (CR) and anterior chamber depth (C-statistic=0.81, 95% CI, 0.73-0.88; C-statistic=0.80, 95% CI, 0.79-0.80, respectively), and axial length/CR (C-statistic=0.78, 95% CI, 0.71-0.85; C-statistic=0.76, 95% CI, 0.75-0.76). With a risk of >70%, the definitions of premyopia indicating approaching myopia onset were 0.00 D for 6-8 years and -0.25 D for ≥9 years in children with 2 myopic parents.
Either cycloplegic refraction or ocular biometry can predict 1-year risk of myopia. Premyopia can be successfully defined through risk assessments based on children's age and predict who would require more aggressive myopia prophylaxis.</abstract><cop>United States</cop><pub>Lippincott Williams & Wilkins</pub><pmid>36706333</pmid><doi>10.1097/APO.0000000000000591</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0002-5721-6051</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Child Cohort Studies Humans Longitudinal Studies Mydriatics Myopia - diagnosis Prospective Studies Refraction, Ocular |
title | Development and Validation of a Model to Predict Who Will Develop Myopia in the Following Year as a Criterion to Define Premyopia |
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