Validating the Accuracy of a Model to Predict the Onset of Myopia in Children METHODS

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1 Clinical and Epidemiologic Research Validating the Accuracy of a Model to redict the Onset of Myopia in Children Mingzhi Zhang, 1 Gus Gazzard, 2 Zhifu Fu, 3 Liping Li, 4 Bin Chen, 1 Seang Mei Saw, 5 and Nathan Congdon 1,6,7 UROSE. To assess the sensitivity and specificity of models predicting myopia onset among ethnically Chinese children. METHODS. Visual acuity, height, weight, biometry (A-scan, keratometry), and refractive error were assessed at baseline and 3 years later using the same equipment and protocol in primary schools in Xiamen (China) and Singapore. A regression model predicting the onset of myopia 0.75 diopters (D) after 3 years in either eye among Xiamen children was validated with Singapore data. RESULTS. Baseline data were collected from 236 Xiamen children (mean age, years) and from 1979 predominantly Chinese children in Singapore ( years). Singapore children were significantly taller and heavier, and had more myopia (31.4% vs. 6.36% 0.75 D in either eye, 0.001) and longer mean axial length. Three-year follow-up was available for 80.0% of Xiamen children and 83.1% in Singapore. For Xiamen, the area under the receiver-operator curve (AUC) in a model including ocular biometry, height, weight, and presenting visual acuity was (95% confidence interval [CI], ). In Singapore, the same model achieved sensitivity, specificity, and positive predictive value of 0.844, 0.650, and 0.669, with an AUC of (95% CI, ). CONCLUSIONS. Accuracy in predicting myopia onset based on simple measurements may be sufficient to make targeted early intervention practical in settings such as Singapore with high myopia prevalence. Models based on cohorts with a greater prevalence of high myopia than that in Xiamen could be used to assess accuracy of models predicting more severe forms of myopia. (Invest Ophthalmol Vis Sci. 2011;52: ) DOI: /iovs Refractive error is the leading cause of poor visual acuity among school-aged children in China 1 4 and has been shown to be associated with significant decrements in visual From the 1 Joint Shantou International Eye Center, Shantou, eople s Republic of China (RC); the 2 Department of Ophthalmology, King s College Hospital, London, United Kingdom; the 3 Mingren Eye Hospital, Anxi, Fujian, RC; the 4 Shantou University College of Medicine, Shantou, RC; the 5 Department of Epidemiology and ublic Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; the 6 Department of Ophthalmology and Visual Sciences, Chinese University of Hong Kong, Hong Kong SAR, RC; and the 7 Zhongshan Ophthalmic Center, State Key Laboratory of Ophthalmology, Sun Yat Sen University, Guangzhou, RC. Supported in part by The Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong. Submitted for publication March 26, 2010; revised July 2, September 22, and December 5 and 23, 2010; accepted December 24, Disclosure: M. Zhang, None; G. Gazzard, None; Z. Fu, None; L. Li, None; B. Chen, None; S.M. Saw, None; N. Congdon, None Corresponding author: Nathan Congdon, Zhongshan Ophthalmic Center, State Key Laboratory and Division of reventive Ophthalmology, Sun Yat Sen University, Guangzhou, RC; ncongdon1@gmail.com. function. 4 Underutilization of spectacles, 3,5 due in part to the false belief that their use will harm children s eyes, 6 together with widespread inaccuracy of presently available correction in rural areas, 7 have contributed to the significant burden of uncorrected and undercorrected refractive error there. Due to these practical limitations in the correction of refractive error with spectacles, and to reduce the risk of various serious ocular conditions associated with increased axial length, 8 11 investigators have examined various modalities to retard myopia progression, including the use of atropine, pirenzepine, corneal reshaping ( orthokeratology ), 18,19 contact lens wear, progressive addition lenses, and deliberate undercorrection of myopic refraction. 26,27 Although some of these modalities, such as pirenzepine, have demonstrated clinically significant reductions in myopia progression with an acceptable side-effect profile, these approaches raise a challenge to program planners: can noninvasive testing performed on emmetropic children at or before the age of highest incidence and most rapid progression of myopia (the early primary school years 28 ) accurately predict children who will later develop myopia? Risk factors for myopia onset and progression have been studied, including younger age of myopia onset, parental education, and refractive error; various biometric factors, including longer axial length and higher corneal power; and female gender and genetic makeup. Although models to predict myopia onset have been reported for Caucasian populations, the sensitivity, specificity, and positive predictive value of such models have not, to the best of our knowledge, been assessed previously among ethnically Chinese children. We report on data from two cohorts of primary school age children followed prospectively with identical protocols for the development of myopia over 3 years. The purposes of the present report were: 1. To develop a model predicting the onset of myopia in the mixed urban rural cohort from Xiamen, southern China. 2. To investigate the sensitivity and specificity of this model in predicting the onset of myopia 0.75 diopters (D) in either eye of a child in the Xiamen cohort after 3 years, based on baseline demographic and biometric data. 3. To test the validity of the model in predicting development of a similar degree of myopia after 3 years in the second cohort of children from Singapore. METHODS The methods of data collection in the Xiamen and Singapore cohorts have been reported elsewhere in detail 40,41 and are reviewed here for reference. Written informed consent was obtained from parents after the nature of the study was explained, and the conduct of the study followed the tenets of the Declaration of Helsinki. Approval was Investigative Ophthalmology & Visual Science, July 2011, Vol. 52, No Copyright 2011 The Association for Research in Vision and Ophthalmology, Inc.

2 IOVS, July 2011, Vol. 52, No. 8 redicting Myopia in Children 5837 obtained from ethics committees at the Singapore National Eye Center and the Xiamen Eye Institute. articipants In Xiamen, children in the second grade of elementary school at two urban and two rural schools were invited to participate, whereas similar-aged children were recruited from three schools in Singapore. articipation rates in Singapore and Xiamen were 62.8% and 91.0%, respectively, and the rates of myopia did not differ between participants and nonparticipants in Singapore. 40 All children recruited in Xiamen were Chinese; in Singapore, 72.5% of children were ethnically Chinese. 40 Children receiving treatment to prevent myopia and those with myopia associated with systemic syndromes or with serious ocular or systemic diseases were excluded. Measurement of Visual Acuity, Refractive Error, and Biometry Children were examined at baseline under the identical protocol in Singapore in November 1999 and in Xiamen in April 2000, supervised by investigators from Singapore. Identical, calibrated equipment was used in both locations. Corrected and uncorrected distance visual acuity was measured in each eye separately using logarithm of minimal angle of resolution (logmar) charts and a standard protocol. 42 Refractive error and corneal curvature (average of five separate measurements) (Canon RK5; Canon Inc. Ltd, Tochigiken, Japan) were measured 30 minutes after cycloplegia with 1% cyclopentolate hydrochloride (3 drops, 5 minutes apart). Ultrasound biometry (Nidek Echoscan US-800; Nidek Co. Ltd, Tokyo, Japan) was performed using the average of six values after anesthesia with 0.5% proparacaine hydrochloride. Measurement of visual acuity, refraction, and ocular biometry were carried out annually using the above-cited protocol over 3 years in both sites. Anthropometric Measurements Height and weight were measured at the schools at baseline. Height was measured with the children standing and without shoes. Weight was measured using a single portable weighing machine calibrated at the beginning of the study. Statistical Methods Statistical analysis software (Statistical ackage for Social Sciences [SSS], version 15.0 for Windows; SSS, Inc., Chicago, IL) was used for analysis. 2 and t-tests were used to analyze difference in visual acuity, height, weight, ocular biometry, and refractive error prevalence between children in the two cohorts. Generalized estimating equations (GEEs) and stepwise GEEs were used to build the model for prediction of the risk for developing spherical equivalent myopia 0.75 D in either eye after 3 years using baseline data among the Xiamen cohort. The same level of myopia ( 0.75 D spherical equivalent in either eye) was used to exclude children with myopia at baseline and to define incident myopia based on observation among children without such myopia at baseline. All demographic, biometric, and vision parameters collected at baseline were considered, with only those variables, squared and cubic terms that were significant, being retained in the final model. Receiver-operating curves (ROCs) showed the sensitivity and specificity of predicting onset of myopia at different risk cutoffs in the model. All children with data at baseline and at 3 years who did not have myopia at baseline were entered into the models. Back substitution, 43 the sample test, 43 and Singapore data were used to test the effectiveness of the model, the latter being used to generate ROC curves for the prediction of myopia in the Singapore cohort at 3 years based on Singapore baseline data and the Xiamen model. Values of 0.05 were considered to be significant throughout. RESULTS Baseline data were collected from 236 children in Xiamen and from 1979 children in Singapore. Although the mean age of the children in the two settings did not differ (Xiamen years, Singapore years, 0.43), Singaporean children were significantly taller and heavier than children in Xiamen, had worse uncorrected logmar visual acuity, and also had a number of biometric traits consistent with myopic refractive error, including longer axial length, and deeper anterior chamber and vitreous chamber depth (Table 1). Myopia 0.75 D in either eye was more prevalent in the Singapore cohort, increasing from 31.4% (621/1979) at baseline (Xiamen 15/ %, 0.001) to 61.7% (1014/ 1644) in the third year (Xiamen 41/ %, 0.001). Refractive information was available for 80.0% (189/236) of children in Xiamen and 83.1% (1644/1979) of children in Singapore at the end of 3 years (Table 2). Among 15 children with myopia at baseline in Xiamen, 11 (73.3%) had 3-year follow-up, as did 467/621 (75.2%) children with baseline myopia in Singapore. Children with myopia at baseline were removed from all analyses predicting the onset of myopia. Additionally, 2 children in Xiamen (both with myopia) and 23 children in Singapore (21 with myopia and 2 without) did not have complete data for modeling. Models predicting the onset of myopia were thus based on 176 children in Xiamen and 1154 in Singapore who were not myopic at baseline and had complete baseline data and refractive measurements at 3-year follow-up. Table 3 shows the characteristics of children in Xiamen and Singapore with complete data who were not myopic at baseline and did or did not go on to develop myopia. In general, TABLE 1. Baseline Characteristics of rimary School Age Children articipating in a rospective Study of Myopia from Xiamen (China) and Singapore Xiamen, China (n 236) Singapore (n 1979) Characteristic Boys Girls Total Boys Girls Total Age, y Weight, kg Height, cm Uncorrected vision, logmar Axial length, mm Anterior chamber depth, mm Lens thickness, mm Vitreous chamber depth, mm Corneal curvature, mm Values are means SD. values compare China and Singapore.

3 5838 Zhang et al. IOVS, July 2011, Vol. 52, No. 8 TABLE 2. Myopia revalence over Time among Cohorts of rimary School-Age Children from Xiamen (China) and Singapore Xiamen, China Singapore Year Number of articipants Number (%) Myopic Number of articipants Number (%) Myopic Baseline (6.36) (31.4) (12.4) (44.2) (15.6) (56.6) (21.7) (61.7) With respect to myopia prevalence, the spherical equivalent is 0.75 D in either eye. values compare China and Singapore. children who were younger, had poorer visual acuity, longer axial length, and longer vitreous chamber depth at baseline were more likely to develop myopia, although differences were not always significant in the smaller Xiamen cohort. Table 4 gives the final GEE model predicting the likelihood of developing myopia 0.75 D in at least one eye by the end of 3 years among children in Xiamen, using baseline gender, height, presenting visual acuity, and biometric measurements obtained from A-scan ultrasonography and keratometry. Only easily measurable parameters were included in this model; information that was collected in the original studies but that might not be readily ascertained in most settings (such as children s birth weight, their time spent in near work) was excluded. Figure 1 depicts the ROC curve for predicting onset of myopia in either eye after 3 years in Xiamen using this model. For example, at a 0.4 probability of developing myopia in the eye, the sensitivity was and the specificity was The area under the ROC curve (AUC) was (95% confidence interval [CI], ). Table 5 depicts the effect of removing each of the parameters included in the model on the AUC, indicating that the accuracy of the model was decreased by any such removal. Each variable was removed singly and all other terms were retained in the model. Terms are listed in order of the size of residual AUC after removal of the term. Figure 2 shows the ROC curve for predicting development of myopia 0.75 D after 3 years in Singapore using the Xiamen model. At the furthest distance from the line of identity on the ROC curve, sensitivity was and specificity 0.650, yielding a positive predictive value of The AUC was ( ). DISCUSSION The goal of the present study was to determine whether it is possible to predict the future development of myopia in young children accurately enough that targeted interventions could practically be used to prevent or slow myopic axial elongation of the globe. The answer to this depends on several factors, including the accuracy, cost, and difficulty of the screening tests, and the prevalence of myopia, an important determinant of positive predictive value. Our results suggest that a predictive algorithm based on results of inexpensive, simple, and noninvasive testing (gender, A-scan ultrasonography, keratometry, and measurements of height and visual acuity) can achieve an acceptable positive predictive value in the range of 75%, at least in a setting such as Singapore, where myopia prevalence is high. It seems likely that such screening and prevention programs would generally be undertaken in settings with a similarly high burden of refractive error. In view of this fact, we chose to test the model in the Singapore cohort, rather than develop it based on Singapore data and test it in the Xiamen cohort, which had lower myopia prevalence. The practicality of strategies for myopia prevention in children rests in part on the efficacy and safety of available treatments. resent modalities have clear limitations, including rebound progression after cessation of medical treatments such as atropine 13 and limited success of refractive strategies such as the use of progressive addition lenses, contact lenses, and deferred prescription of corrective spectacles. 26,27 Nonetheless, research is ongoing on the efficacy of compounds such as selective -aminobutyric acid type C antagonists in retarding axial elongation in animal models 44,45 ; the question of whether TABLE 3. Characteristics of Children with Complete Data and without Myopia at Baseline in Xiamen and Singapore Who Did and Did Not Go on to Develop Myopia by 3-Year Follow-up Xiamen (n 176) Singapore (n 1154) Factor Developed Myopia (n 28) Did Not Develop Myopia (n 148) Developed Myopia (n 526) Did Not Develop Myopia (n 628) Age, y Weight, kg Height, cm Visual acuity, logmar Axial length, mm <0.001 Anterior chamber depth, mm Lens thickness, mm Vitreous chamber depth, mm <0.001 Corneal curvature, mm Bold values indicate statistical significance at the 0.05 level.

4 IOVS, July 2011, Vol. 52, No. 8 redicting Myopia in Children 5839 TABLE 4. Generalized Estimating Equation Model redicting Myopia after 3 Years of Follow-up among 176 rimary School-Age Children in Xiamen, China TABLE 5. Impact on AUC of Removing Each of the Variables Included in the Model redicting Onset of Myopia Based on Children in Xiamen without Myopia at Baseline redictor Beta SE Factor Removed AUC (95% CI) Female gender Height, cm Visual, logmar Vision Vision 3 Axial length (AL), mm AL AL Anterior chamber depth (ACD), mm ACD ACD Lens thickness (LT), mm LT LT LT Vitreous chamber depth (VCD), mm VCD VCD Corneal curvature (CC), mm CC CC ACD LT VCD With respect to predicting myopia, the spherical equivalent refractive error is 0.75 D. screening accuracy will limit the practical applications of such advances in the prevention of human myopia remains relevant. The values for sensitivity, specificity, and AUC in the Singapore test cohort are somewhat lower than those reported by Zadnik et al. 39 for a model using baseline refractive error to predict onset of myopia 0.75 D within the Orinda Longitudinal Study of Myopia (sensitivity, 0.867; specificity, 0.733; Original model* ( ) Gender removed ( ) Visual acuity removed ( ) Height removed ( ) Anterior chamber depth removed ( ) Vitreous chamber depth removed ( ) Lens thickness removed ( ) Corneal curvature removed ( ) Axial depth removed ( ) Because each variable was removed singly, all other variables remained in the model. * Original model includes gender, height, visual acuity, axial length, anterior chamber depth, lens thickness, vitreous chamber depth, and corneal curvature. AUC, 0.880). Jones-Jordan et al. 38 reported values comparable to ours (sensitivity, 0.625; specificity, 0.819) for a model using myopia at baseline and parental history of myopia to predict the onset of myopia 0.75 D in the Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error Study. Unlike these studies, the present report used one cohort (Xiamen) to develop a model and another (Singapore) to test it. Although our model was somewhat more complex than that reported by Zadnik and colleagues, 39 our analyses (Table 5) suggest that removal of any of the variables from the model reduced its performance as measured by the AUC. Applying Zadnik s model to the Xiamen data set yielded an AUC of 0.711, considerably reduced from a value of for our original model. Unlike the Zadnik model, the baseline spherical equivalent refractive error was not an important predictor in the present study. Our results indicating that female gender is associated with myopia risk are consistent with other studies in Chinese populations. 30,31 FIGURE 1. ROC curve for prediction of myopia 0.75 D spherical equivalent after 3 years of follow-up among primary school age children in Xiamen China (area under the ROC curve [AUC], 0.974; 95% CI, ). FIGURE 2. ROC curve for prediction of myopia 0.75 D spherical equivalent after 3 years of follow-up among primary school age children in Singapore (AUC, 0.815; 95% CI, ).

5 5840 Zhang et al. IOVS, July 2011, Vol. 52, No. 8 Significantly increased risk for development of glaucoma, 10 cataract, 9 and retinal detachment 8 appears most pronounced at higher powers of myopic refractive error. Thus, in practice, there will likely be the greatest interest in early prediction and prevention of high myopia. The model in the present study was constrained by the absence of myopia in this range in the Xiamen cohort on which calculations were based, and thus focused on the ascertainment of myopia 0.75 D. Children reaching this level of myopia by 11 years of age might be expected to subsequently progress to higher, more visually significant levels. Still, future prospective studies using comparable protocols in matched cohorts with greater prevalence of high myopia are needed to develop and test models predicting the onset of high myopia. Such models will likely benefit from higher sensitivity and specificity, in that there will be less overlap of baseline biometric characteristics between normal children and those who will later develop high myopia. However, the positive predictive value will likely be reduced by the lower prevalence of high compared with low myopia. It is unknown at present how the balance of these two influences will affect predictive value, and thus the practical utility, of models for high myopia. arental myopia appears in other studies 30,33,38 to be an important determinant of children s myopia progression, and thus might improve the accuracy of predictive models; this would, however, come at the cost of added complexity in the screening process, which might render the collection of such data impractical in many settings. In many parts of China, for example, a history of glasses wear, as has been used as a simple proxy for parental myopia in some studies, will not be useful in view of low rates of spectacle wear among myopic persons. The same may be true for detailed assessment of near work, 40,46 48 outdoor activity, 49 and genetic makeup, 34 also previously reported as risk factors for myopia and myopia progression. The strengths of this study include the validation of our model by replication in a Singapore cohort, in which data were gathered using the identical protocol and equipment as those used in the original Xiamen children. In each of these two quite different locations, a high degree of follow-up was achieved over 3 years. Both the settings and the screening modalities used are relevant to the practical problem of myopia screening: Singapore and China have very high burdens of myopic refractive error and all the tests used are widely available, inexpensive, and noninvasive. The high rate of success in data collection within the original studies indicates that screening of all children at entry to elementary school, for example, could be practical in a setting with high myopia prevalence such as Singapore or urban China. Weaknesses of the study include the complexity of the model. The use of squared and cubed terms and interaction variables means that risk of myopia does not vary in an intuitively clear way with biometric factors such as axial length and corneal curvature. However, the purpose of this model was to predict future myopia in an eye as accurately as possible, and not to better understand risk factors for myopia. An additional limitation noted earlier is that a model predicting onset of higher degrees of myopia, not practical with the Xiamen cohort, would have been more relevant to the screening problems facing program planners hoping to decrease the visual burden of myopia. 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