Browsing by Author "Hoang, Quan V."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- Deep learning system to predict the 5-year risk of high myopia using fundus imaging in childrenPublication . Foo, Li Lian; Lim, Gilbert Yong San; Lança, Carla; Wong, Chee Wai; Hoang, Quan V.; Zhang, Xiu Juan; Yam, Jason C.; Schmetterer, Leopold; Chia, Audrey; Wong, Tien Yin; Ting, Daniel S. W.; Saw, Seang-Mei; Ang, MarcusOur study aims to identify children at risk of developing high myopia for timely assessment and intervention, preventing myopia progression and complications in adulthood through the development of a deep learning system (DLS). Using a school-based cohort in Singapore comprising 998 children (aged 6-12 years old), we train and perform primary validation of the DLS using 7456 baseline fundus images of 1878 eyes; with external validation using an independent test dataset of 821 baseline fundus images of 189 eyes together with clinical data (age, gender, race, parental myopia, and baseline spherical equivalent (SE)). We derive three distinct algorithms - image, clinical, and mix (image + clinical) models to predict high myopia development (SE ≤ -6.00 diopter) during teenage years (5 years later, age 11-17). Model performance is evaluated using the area under the receiver operating curve (AUC). Our image models (Primary dataset AUC 0.93-0.95; Test dataset 0.91-0.93), clinical models (Primary dataset AUC 0.90-0.97; Test dataset 0.93-0.94) and mixed (image + clinical) models (Primary dataset AUC 0.97; Test dataset 0.97-0.98) achieve clinically acceptable performance. The addition of 1 year SE progression variable has minimal impact on the DLS performance (clinical model AUC 0.98 versus 0.97 in the primary dataset, 0.97 versus 0.94 in the test dataset; mixed model AUC 0.99 versus 0.97 in the primary dataset, 0.95 versus 0.98 in test dataset). Thus, our DLS allows prediction of the development of high myopia by teenage years amongst school-going children. This has potential utility as a clinical decision support tool to identify "at-risk" children for early intervention.
- New polygenic risk score to predict high myopia in Singapore Chinese childrenPublication . Lança, Carla; Kassam, Irfahan; Patasova, Karina; Foo, Li-Lian; Li, Jonathan; Ang, Marcus; Hoang, Quan V.; Teo, Yik-Ying; Hysi, Pirro G.; Saw, Seang-MeiPurpose: The purpose of this study was to develop an Asian polygenic risk score (PRS) to predict high myopia (HM) in Chinese children in the Singapore Cohort of Risk factors for Myopia (SCORM) cohort. Methods: We included children followed from 6 to 11 years old until teenage years (12–18 years old). Cycloplegic autorefraction, ultrasound biometry, Illumina HumanHap 550, or 550 Duo Beadarrays, demographics, and environmental factors data were obtained. The PRS was generated from the Consortium for Refractive Error and Myopia genomewide association study (n = 542,934) and the Strabismus, Amblyopia, and Refractive Error in Singapore children Study (n = 500). The Growing Up in Singapore Towards healthy Outcomes Cohort study (n = 339) was the replication cohort. The outcome was teenage HM (≤ −5.00 D) with predictive performance assessed using the area under the curve (AUC). Results: Mean baseline age ± SD was 7.85 ± 0.84 (n = 1004) and 571 attended the teenage visit; 23.3% had HM. In multivariate analysis, the PRS was associated with a myopic spherical equivalent with an incremental R2 of 0.041 (95% confidence interval [CI] = 0.010, 0.073; P < 0.001). AUC for HM (0.77 [95% CI = 0.71–0.83]) performed better (P = 0.02) with the PRS compared with a model without (0.72 [95% CI = 0.65, 0.78]). Children at the top 25% PRS risk had a 2.34-fold-greater risk of HM (95% CI = 1.53, 3.55; P < 0.001). Conclusions: The new Asian PRS improved the predictive performance to detect children at risk of HM.
- The potential of current polygenic risk scores to predict high myopia and myopic macular degeneration in multi-ethnic Singapore adultsPublication . Kassam, Irfahan; Foo, Li-Lian; Lança, Carla; Xu, Ling Qian; Hoang, Quan V.; Cheng, Ching-Yu; Hysi, Pirro; Saw, Seang-MeiPurpose: To evaluate the trans-ancestry portability of current myopia polygenic risk scores (PRS) to predict high myopia (HM) and myopic macular degeneration (MMD) in an Asian population. Design: Population-based study. Subjects: A total of 5,894 (2,141 Chinese, 1,913 Indians, and 1,840 Malays) adults from the Singapore Epidemiology of Eye Diseases (SEED) study were included in the analysis. The mean age was 57.0 (standard deviation, SD = 9.31) years. A total of 361 adults had HM (spherical equivalent, SE <-5.00D) from refraction measurements, 240 individuals were diagnosed with MMD graded by the Meta-PM criteria from fundus photographs, and 3,774 individuals were controls without myopia (SE >-0.5D). Methods: The PRS, derived from 687,289 HapMap3 SNPs from the largest genome-wide association study of myopia in Europeans to date (n = 260,974), was assessed on its ability to predict HM and MMD versus controls. Main outcome measures: The primary outcomes were the area under the receiver operating characteristic curve (AUROC) to predict HM and MMD. Results: The PRS had an AUROC of 0.73 (95% CI: 0.70, 0.75) for HM and 0.66 (95% CI: 0.63, 0.70) for MMD versus no myopia controls. The inclusion of the PRS with other predictors (age, sex, educational attainment (EA), and ancestry; age-by-ancestry; sex-by-ancestry and EA-by-ancestry interactions; and 20 genotypic principal components) increased the AUROC to 0.84 (95% CI: 0.82, 0.86) for HM and 0.79 (95% CI: 0.76, 0.82) for MMD. Individuals with a PRS in the top 5% had 4.66 (95% CI: 3.34, 6.42) times higher risk for HM and 3.43 (95% CI: 2.27, 5.05) times higher risk for MMD compared to the remaining 95% of individuals. Conclusion: The PRS is a good predictor for HM and will facilitate the identification of high-risk children to prevent myopia progression to HM. In addition, the PRS also predicts MMD and will help to identify high-risk myopic adults who require closer monitoring for myopia-related complications.