Development and Validation of a Model to Predict Who Will Develop Myopia in the Following Year as a Criterion to Define Premyopia.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Association of time outdoors and patterns of light exposure with myopia in children.

BACKGROUND/AIMS: To evaluate the association of reported time outdoors and light exposure patterns with myopia among children aged 9 years from the Growing Up in Singapore Towards Healthy Outcomes birth cohort. METHODS: We assessed reported time outdoors (min/day), light exposure patterns and outdoor activities of children aged 9 years (n=483) with a questionnaire, the FitSight watch and a 7-day activity diary. Light levels, the duration, timing and frequency of light exposure were assessed. Cycloplegic spherical equivalent (SE), myopia (SE≤-0.5 D) and axial length (AL) of paired eyes were analysed using generalised estimating equations. RESULTS: In this study, 483 (966 eyes) multiethnic children (50.0% boys, 59.8% Chinese, 42.2% myopic) were included. Reported time outdoors (mean±SD) was 100±93 min/day, and average light levels were 458±228 lux. Of the total duration children spent at light levels of ≥1000 lux (37±19 min/day), 76% were spent below 5000 lux. Peak light exposure occurred at mid-day. Children had 1.7±1.0 light exposure episodes/day. Common outdoor activities were walks, neighbourhood play and swimming. Greater reported time outdoors was associated with lower odds of myopia (OR=0.82, 95% CI 0.70 to 0.95/hour increase daily; p=0.009). Light levels, timing and frequency of light exposures were not associated with myopia, SE or AL (p>0.05). CONCLUSION: Reported time outdoors, light levels and number of light exposure episodes were low among Singaporean children aged 9 years. Reported time outdoors was protective against myopia but not light levels or specific light measures. A multipronged approach to increase time outdoors is recommended in the combat against the myopia epidemic.

Pathologic myopia: advances in imaging and the potential role of artificial intelligence.

Pathologic myopia is a severe form of myopia that can lead to permanent visual impairment. The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. In this review, we provide an update on the classification of pathologic myopia, how imaging has improved clinical evaluation and management of myopia-associated complications, and the recent development of AI algorithms to aid the detection and classification of pathologic myopia.

Systematic Review and Meta-Analysis on the Impact of COVID-19 Pandemic-Related Lifestyle on Myopia.

PURPOSE: To conduct a systematic review and meta-analysis to assess the effects of coronavirus disease 2019 (COVID-19) pandemic-related lifestyle on myopia outcomes in children to young adults. METHODS: A systematic search was conducted on PubMed, Embase, and the Cochrane Central Register of Controlled Trials databases (with manual searching of reference lists of reviews). Studies included assessed changes in myopia-related outcomes (cycloplegic refraction) during COVID and pre-COVID. Of 367 articles identified, 7 (6 prospective cohorts; 1 repeated cross-sectional study) comprising 6327 participants aged 6 to 17 were included. Quality appraisals were performed with Joanna Briggs Institute Critical Appraisal Checklists. Pooled differences in annualized myopic shifts or mean spherical equivalent (SE) during COVID and pre-COVID were obtained from random-effects models. RESULTS: In all 7 studies, SE moved toward a myopic direction during COVID (vs pre-COVID), where 5 reported significantly faster myopic shifts [difference in means of changes: -1.20 to -0.35 diopters per year, [D/y]; pooled estimate: -0.73 D/y; 95% confidence interval (CI): -0.96, -0.50; P<0.001], and 2 reported significantly more myopic SE (difference in means: -0.72 to -0.44 D/y; pooled estimate: -0.54 D/y; 95% CI: -0.80, -0.28; P<0.001). Three studies reported higher myopia (SE ≤-0.50 D) incidence (2.0- to 2.6-fold increase) during COVID versus pre-COVID. Of studies assessing lifestyle changes, all 4 reported lower time outdoors (pre-COVID vs during COVID: 1.1-1.8 vs 0.4-1.0 hours per day, [h/d]), and 3 reported higher screen time (pre-COVID vs during COVID: 0.7-2.8 vs 2.4-6.9 h/d). CONCLUSIONS: This review suggests more myopic SE shifts during COVID (vs pre-COVID) in participants aged 6 to 17. COVID-19 restrictions may have worsened SE shifts, and lifting of restrictions may lessen this effect. Evaluations of the long-term effects of the pandemic lifestyle on myopia onset and progression in large studies are warranted to confirm these findings.

Sleep Patterns and Myopia Among School-Aged Children in Singapore.

Purpose: To evaluate the associations of sleep factors with myopia, spherical equivalent (SE), and axial length (AL) in elementary school-aged children from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort. Methods: This cross-sectional study included multi-ethnic children who participated in the GUSTO prospective birth cohort and were delivered in two major tertiary hospitals in Singapore (2009-2010). Sleep factors and myopia outcomes were assessed at the 8- and 9-year study visits, respectively. Parent-reported sleep quality was assessed with the Children's Sleep Habits Questionnaire (CSHQ) total scores. Additionally, each child's sleep duration, timing (bedtime; waketime), and the consistency of sleep duration or timing (i.e., the difference between weekends and weekdays) were parent-reported. Outcomes included cycloplegic SE, myopia (SE ≤ -0.5 D) and AL. Eye measurements from both eyes were included in the analyses. Multivariable linear or logistic regression with Generalized Estimating Equations were used to account for the correlation between paired eyes and confounders in the associations of sleep factors at age 8 and myopia at age 9. Results: A total of 572 multi-ethnic children (49.5% boys; 56.1% Chinese) aged 9 years were included in the analyses. Overall, 37.3% of eyes were myopic. Children reported a mean total CSHQ score of 46 [standard deviation (SD) = 6]. The mean duration of sleep was 9.2 (SD = 1.0) hours per day (h/day), with 59.9% of children reporting sufficient sleep (≥9 h/day) based on guidelines recommended by the National Sleep Foundation, USA. The mean bedtime and wake time were 22:00 (SD = 00:53) and 07:08 (SD = 00:55), respectively. In multivariable regression models, total CSHQ scores, the duration of sleep, bedtime and wake time were not significantly associated with myopia, SE, or AL (p ≥ 0.05 for all), adjusting for gender, ethnicity, time outdoors, near-work, parental myopia, maternal education levels (and additionally the child's height when the outcome was AL). Similarly, the consistency of both the duration and timing of sleep (across weekends and weekdays) were not significantly associated with myopia, SE, or AL (p ≥ 0.05 for all). Conclusion: In this cross-sectional study, sleep quality, duration, timing, and the consistency of specific sleep factors were not independently associated with myopia, SE, or AL among elementary school-aged children in Singapore. Large longitudinal studies are warranted to corroborate these results.

The Potential of Current Polygenic Risk Scores to Predict High Myopia and Myopic Macular Degeneration in Multiethnic Singapore Adults.

PURPOSE: To evaluate the transancestry portability of current myopia polygenic risk scores (PRSs) to predict high myopia (HM) and myopic macular degeneration (MMD) in an Asian population. DESIGN: Population-based study. PARTICIPANTS: A total of 5894 adults (2141 Chinese, 1913 Indian, and 1840 Malay) from the Singapore Epidemiology of Eye Diseases study were included in the analysis. The mean ± standard deviation age was 57.05 ± 9.31 years. A total of 361 adults had a diagnosis of HM (spherical equivalent [SE] < -5.00 diopters [D]) from refraction measurements, 240 individuals had a diagnosis of MMD graded by the International Photographic Classification and Grading System for Myopic Maculopathy criteria from fundus photographs, and 3774 individuals were control participants without myopia (SE > -0.5 D). METHODS: The PRS, derived from 687 289 HapMap3 single nucleotide polymorphisms (SNPs) from the largest genome-wide association study of myopia in Europeans to date (n = 260 974), was assessed on its ability to predict patients with HM and MMD versus control participants. MAIN OUTCOME MEASURES: The primary outcomes were the area under the receiver operating characteristic curve (AUC) to predict HM and MMD. RESULTS: The PRS had an AUC of 0.73 (95% confidence interval [CI], 0.70-0.75) for HM and 0.66 (95% CI, 0.63-0.70) for MMD versus no myopia. 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 AUC 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% showed up to a 4.66 (95% CI, 3.34-6.42) times higher risk of HM developing and up to a 3.43 (95% CI, 2.27-5.05) times higher risk of MMD developing compared with the remaining 95% of individuals. CONCLUSIONS: The PRS is a good predictor for HM and facilitates the identification of high-risk children to prevent myopia progression to HM. In addition, the PRS also predicts MMD and helps to identify high-risk adults with myopia who require closer monitoring for myopia-related complications.

Dietary intake and associations with myopia in Singapore children.

PURPOSE: To evaluate associations of dietary factors with myopia, spherical equivalent refractive error (SE) and axial length (AL) in children at age 9 from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) birth cohort. METHODS: We included 467 multi-ethnic children (933 eyes) who participated in the GUSTO prospective birth cohort and were delivered in two major hospitals in Singapore (2009-2010). At the 9-year visit, we assessed the 6-year incidence of myopia (between ages 3 to 9), cycloplegic SE and AL in children without myopia (SE ≤ -0.5 D in either eye) at the 3-year visit. Using a validated 112-item food frequency questionnaire, parents reported each child's average daily intake of dietary factors (nutrients and food groups) in the past month. Paired eyes were analysed using Generalised Estimating Equations with multivariable logistic or linear regression. Bonferroni corrections were applied, correcting for multiple comparisons between the 13 nutrients (p < 0.004) or 8 food groups (p < 0.006) and each outcome. RESULTS: In children aged 9 years (51.0% boys; 56.3% Chinese), the 6-year incidence of myopia was 35.5%. Overall, the mean (SD) SE and AL were -0.3 (1.7) D and 23.4 (1.0) mm, respectively. In multivariable regression, macronutrients or micronutrients were not associated with incident myopia (p ≥ 0.004 for all), adjusting for total energy, gender, ethnicity, time outdoors, near-work and the number of myopic parents (additionally child's height for outcome AL). Similarly, all food groups (including refined grains, sugar-sweetened beverages, protein foods, fruits and vegetables) were not associated with incident myopia (p ≥ 0.006 for all). Additionally, none of the nutrients (p ≥ 0.004 for all) or food groups (p ≥ 0.006 for all) were associated with SE or AL. CONCLUSIONS: Our study findings of no significant association between specific nutrients or food groups and incident myopia or SE or AL suggest that diet may not be associated with myopia in children aged 9 years. Well-conducted prospective studies in other populations may clarify the association.

New Polygenic Risk Score to Predict High Myopia in Singapore Chinese Children.

Purpose: 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. Translational Relevance: Clinicians may use the PRS with other predictive factors to identify high risk children and guide interventions to reduce the risk of HM later in life.

Rapid Myopic Progression in Childhood Is Associated With Teenage High Myopia.

Purpose: The purpose of this study was to evaluate the association of childhood progression of spherical equivalent (SE) with high myopia (HM) in teenagers in the Singapore Cohort of Risk factors for Myopia (SCORM). Methods: We included 928 SCORM children followed over a mean follow-up of 6.9 ± 1.0 years from baseline (6-11 years old) until their teenage years (12-19 years old). Cycloplegic autorefraction and axial length (AL) measurements were performed yearly. The outcomes in teenagers were HM (SE ≤ -5 diopter [D)], AL ≥ 25 mm, SE and AL. Three-year SE and AL progression in childhood and baseline SE and AL with outcomes were evaluated using multivariable logistic or linear regression models, with predictive performance of risk factors assessed using the area under the curve (AUC). Results: At the last visit, 9.8% of teenagers developed HM and 22.7% developed AL ≥ 25 mm. In multivariate regression analyses, every -0.3 D/year increase in 3-year SE progression and every 0.2 mm/year increase in 3-year AL progression were associated with a -1.14 D greater teenage SE and 0.52 mm greater teenage AL (P values < 0.001). The AUC (95% confidence interval [CI]) of a combination of 3-year SE progression and baseline SE for teenage HM was 0.97 (95% CI = 0.95 - 0.98). The AUC of 3-year AL progression and baseline AL for teenage AL ≥ 25 mm was 0.91 (95% CI = 0.89 - 0.94). Conclusions: Three-year myopia progression in childhood combined with baseline SE or AL were good predictors of teenage HM. Clinicians may use this combination of factors to guide timing of interventions, potentially reducing the risk of HM later in life.

Subgrouping of primary angle-closure suspects based on anterior segment optical coherence tomography parameters.

PURPOSE: To identify subgroups of primary angle-closure suspects (PACS) based on anterior segment optical coherence tomography (AS-OCT) and biometric parameters. DESIGN: Cross-sectional study. PARTICIPANTS: We evaluated 243 PACS subjects in the primary group and 165 subjects in the validation group. METHODS: Participants underwent gonioscopy and AS-OCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure AS-OCT parameters. An agglomerative hierarchical clustering method was first used to determine the optimum number of parameters to be included in the determination of subgroups. The best number of subgroups was then determined using Akaike Information Criterion (AIC) and Gaussian Mixture Model (GMM) methods. MAIN OUTCOME MEASURES: Subgroups of PACS. RESULTS: The mean age of the subjects was 64.8 years, and 65.02% were female. After hierarchical clustering, 1 or 2 parameters from each cluster were chosen to ensure representativeness of the parameters and yet keep a minimum of redundancy. The parameters included were iris area, anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV). With the use of GMM, the optimal number of subgroups as given by AIC was 3. Subgroup 1 was characterized by a large iris area, subgroup 2 was characterized by a large LV and a shallow ACD, and subgroup 3 was characterized by elements of both subgroups 1 and 2. The results were replicated in a second independent group of 165 PACS subjects. CONCLUSIONS: Clustering analysis identified 3 distinct subgroups of PACS subjects based on AS-OCT and biometric parameters. These findings may be relevant for understanding angle-closure pathogenesis and management.

Associations of iris structural measurements in a Chinese population: the Singapore Chinese Eye Study.

PURPOSE: We determined the ocular biometric and demographic factors associated with iris parameters in Singaporean Chinese persons from a population-based sample. METHODS: Subjects were participants in the Singapore Chinese Eye Study, a population-based cross-sectional study of eye disease. Anterior segment optical coherence tomography images were analyzed using customized software to measure iris thickness at 750 µm from the scleral spur (IT750), iris area (I-Area), and iris curvature (I-Curv). Regression analyses were performed to assess the association between iris measurements with a range of demographic and ocular variables. The contribution of each independent variable to the iris parameter of interest was determined sequentially using a stepwise selection algorithm. RESULTS: We included 1473 participants with a mean age of 57.7 + 8.68 years, and 50.6% were men. The mean IT750, I-Area, and I-Curv were 0.46 ± 0.10 mm, 1.49 ± 0.24 mm(2), and 0.25 ± 0.13 mm, respectively. Statistical regression models, including a range of demographic and ocular parameters, explained 59.3%, 41.9%, and 34.3% of the variability in I-Curv, IT750, and I-Area, respectively. Angle opening distance at 750 µm from the scleral spur (AOD750) was the single factor associated most strongly with I-Curv, and explained 46.6% of its variation. CONCLUSIONS: A significant proportion of the variation in iris area, curvature, and thickness was not explained by other ocular and demographic parameters. Iris curvature was associated strongly with angle width, and of all parameters investigated, AOD750 was most highly correlated with iris curvature.

Classification algorithms based on anterior segment optical coherence tomography measurements for detection of angle closure.

OBJECTIVE: A recent study found that a combination of 6 anterior segment optical coherence tomography (ASOCT) parameters (anterior chamber area, volume, and width [ACA, ACV, ACW], lens vault [LV], iris thickness at 750 µm from the scleral spur, and iris cross-sectional area) explain >80% of the variability in angle width. The aim of this study was to evaluate classification algorithms based on ASOCT measurements for the detection of gonioscopic angle closure. DESIGN: Cross-sectional study. PARTICIPANTS: We included 2047 subjects aged ≥50 years. METHODS: Participants underwent gonioscopy and ASOCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters in horizontal ASOCT scans. Six classification algorithms were considered (stepwise logistic regression with Akaike information criterion, Random Forest, multivariate adaptive regression splines, support vector machine, naïve Bayes' classification, and recursive partitioning). The ASOCT-derived parameters were incorporated to generate point and interval estimates of the area under the receiver operating characteristic (AUC) curves for these algorithms using 10-fold cross-validation as well as 50:50 training and validation. MAIN OUTCOME MEASURES: We assessed ASOCT measurements and angle closure. RESULTS: Data on 1368 subjects, including 295 (21.6%) subjects with gonioscopic angle closure were available for analysis. The mean (±standard deviation) age was 62.4±7.5 years and 54.8% were females. Angle closure subjects were older and had smaller ACW, ACA, and ACV; greater LV; and thicker irides (P<0.001 for all). For both, the 10-fold cross-validation and the 50:50 training and validation methods, stepwise logistic regression was the best algorithm for detecting eyes with gonioscopic angle closure with testing set AUC of 0.954 (95% confidence interval [CI], 0.942-0.966) and 0.962 (95% CI, 0.948-0.975) respectively, whereas recursive partitioning had relatively the poorest performance with testing set AUC 0.860 (95% CI, 0.790-0.930) and 0.905 (95% CI, 0.876-0.933), respectively. This algorithm performed similarly well (AUC, 0.957) in a second independent sample of 200 angle closure subjects and 302 normal controls. CONCLUSIONS: A classification algorithm based on stepwise logistic regression that used a combination of 6 parameters obtained from a single horizontal ASOCT scan identified subjects with gonioscopic angle closure>95% of the time. FINANCIAL DISCLOSURE(S): The authors have no proprietary or commercial interest in any of the materials discussed in this article.

Determinants of anterior chamber depth: the Singapore Chinese Eye Study.

PURPOSE: Recent advances in anterior segment imaging have enabled the measurement of novel ocular biometric parameters, such as lens vault (LV), posterior corneal arc length (PCAL), and iris area. The aims of this study were to identify the determinants of anterior chamber depth (ACD) and to ascertain the relative importance of these determinants in Chinese persons in Singapore. DESIGN: Population-based, cross-sectional study. PARTICIPANTS: One thousand sixty Chinese participants recruited from the Singapore Chinese Eye Study. METHODS: All subjects underwent AS optical coherence tomography (OCT; Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure the AS-OCT parameters. Anterior chamber depth was determined using IOLMaster (Carl Zeiss Meditec). Univariate and multivariate regression analyses were performed to assess the association between ACD with ocular biometric and systemic parameters. A stepwise selection algorithm was used to identify sequentially the contribution of each independent variable. MAIN OUTCOME MEASURES: Anterior chamber depth and ocular biometric parameters. RESULTS: The mean age (±standard deviation) of participants was 56.9±8.57 years and 50.5% were men. The mean ACD was 3.24±0.35 mm. The strongest determinants of ACD were LV (R(2) = 0.582; P<0.001) and PCAL (partial R(2) = 0.186; P<0.001). For every 10-µm increase in LV and every 1-mm increase in PCAL, ACD changed by -0.008 mm (95% confidence interval [CI], -0.009 to -0.008 mm; P<0.001) and 0.525 mm (95% CI, 0.468-0.583 mm; P<0.001), respectively. The 8 most highly associated variables (including LV, PCAL, axial length, age, and iris area) explained 80.5% of the variability in ACD, but when excluding LV and PCAL, the other 6 variables explained only 3.7% of the variability in ACD. After controlling for LV and PCAL, axial length was a poor determinant of ACD (partial R(2) = 0.006), whereas lens thickness was not associated independently with ACD. CONCLUSIONS: Lens vault and PCAL explained 76.8% of the variability in ACD. When information about LV and PCAL were available, axial length was a poor determinant of ACD, whereas lens thickness was not associated independently with ACD. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Comparison of scanning laser ophthalmoscopy and high-definition optical coherence tomography measurements of optic disc parameters.

OBJECTIVE: To investigate the agreement between scanning laser ophthalmoscopy (Heidelberg retinal tomograph 3; HRT-3) and high-definition optical coherence tomography (HD-OCT) for measurements of optic nerve head (ONH) parameters. METHODS: As part of a population-based cross-sectional study, 913 consecutive Chinese subjects aged 40 years and older underwent HRT-3 and HD-OCT imaging of the ONH after pupillary dilation. Limits of agreement (LOA) derived from Bland-Altman analysis were calculated for ONH measurements. RESULTS: The mean age (± SD) of study participants was 54.2 ± 7.2 years and 52.0% were men. The two instruments showed no difference in mean optic disc area measurements (1.98 ± 0.37 for HD-OCT vs 1.98 ± 0.39 mm for HRT-3, p=0.95). HD-OCT showed smaller rim area (1.29 ± 0.24 vs 1.46 ± 0.27 mm, p<0.001), but bigger cup-related parameters (p<0.001 for all) than HRT-3. The highest correlations between the instruments were observed for cup volume (r(2)=0.74, p<0.001) and disc area (r(2)=0.62, p<0.001). The correlations for cup-to-disc ratio (CDR), vertical CDR and rim area were lower (r(2)=0.59, 0.48 and 0.24, respectively, p<0.001 for all). The Bland-Altman plots demonstrated significant proportional bias for differences in all ONH parameters (p<0.01 for all), with LOA greater for disc-related parameters (0.98-1.0) than cup-related parameters (0.26-0.50). CONCLUSIONS: There are substantial disagreements between HRT-3 and HD-OCT in ONH measurements. Although optic disc area measurements were similar, HD-OCT underestimates the rim area and overestimates cup parameters compared with HRT-3.

Determinants of angle width in Chinese Singaporeans.

PURPOSE: To investigate determinants of angle width and derive mathematic models to best predict angle width. DESIGN: Population-based, cross-sectional study. PARTICIPANTS: A total of 1067 Chinese subjects aged ≥40 years. METHODS: Participants underwent gonioscopy, A-scan biometry, and imaging by anterior segment optical coherence tomography (ASOCT, Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters. Linear regression modeling was performed with trabecular-iris space area at 750 µm (TISA750) and angle opening distance at 750 µm (AOD750) from the scleral spur as the 2 dependent angle width variables. By using a combination of ASOCT and biometric parameters, an optimal model that was predictive of angle width was determined by a forward selection regression algorithm. Validation of the results was performed in a separate set of community-based clinic study of 1293 persons aged ≥50 years. MAIN OUTCOME MEASURES: Angle width and biometric parameters. RESULTS: The mean age (standard deviation) of the population-based subjects was 56.9 (8.5) years, and 50.2% were male. For TISA750, the strongest determinants among ASOCT and A-scan independent variables were anterior chamber volume (ACV, R(2)=0.51), followed by anterior chamber area (ACA, R(2)=0.49) and lens vault (LV, R(2)=0.47); for AOD750, these were LV (R(2)=0.56), ACA (R(2)=0.55), and ACV (R(2)=0.54). The R(2) values for anterior chamber depth and axial length were 0.39 and 0.27 for TISA750, respectively, and 0.46 and 0.30 for AOD750, respectively. An optimal model consisting of 6 variables (ACV, ACA, LV, anterior chamber width [ACW], iris thickness at 750 µm, and iris area) explained 81.4% of the variability in TISA750 and 85.5% of the variability in AOD750. The results of the population-based study were validated in the community-based clinic study, where the strongest determinants of angle width (ACA, ACV, and LV) and the optimal model with 6 variables were similar. CONCLUSIONS: Angle width is largely dependent on variations in ACA, ACV, and LV. A predictive model comprising 6 quantitative ASOCT parameters explained more than 80% of the variability of angle width and may have implications for screening for angle closure.

Survival outcome of women with synchronous cancers of endometrium and ovary: a 10 year retrospective cohort study.

OBJECTIVE: Synchronous occurrence of endometrial and ovarian tumors is uncommon, and they affect less than 10% of women with endometrial or ovarian cancers. The aim of this study is to describe the epidemiological and clinical factors; and survival outcomes of women with these cancers. METHODS: This is a retrospective cohort study in a large tertiary institution in Singapore. The sample consists of women with endometrial and epithelial ovarian cancers followed up over a period of 10 years from 2000 to 2009. The epidemiological and clinical factors include age at diagnosis, histology types, grade and stage of disease. RESULTS: A total of 75 patients with synchronous ovarian and endometrial cancers were identified. However, only 46 patients met the inclusion criteria. The median follow-up was 74 months. The incidence rate for synchronous cancer is 8.7% of all epithelial ovarian cancers and 4.9% of all endometrial cancers diagnosed over this time frame. Mean age at diagnosis was 47.3 years old. The most common presenting symptom was abnormal uterine bleeding (36.9%) and 73.9% had endometrioid histology for both endometrial and ovarian cancers. The majority of the women (78%) presented were at early stages of 1 and 2. There were 6 (13.6%) cases of recurrence and the 5 year cumulative survival rate was at 84%. CONCLUSION: In our cohort, we found that majority of women afflicted with synchronous cancer of the endometrium and ovary were younger at age of diagnosis, had early stage of cancer and good survival.