Polygenic Risk Scores for Glaucoma Onset in the Ocular Hypertension Treatment Study.

Importance: Primary open-angle glaucoma (POAG) is a highly heritable disease, with 127 identified risk loci to date. Polygenic risk score (PRS) may provide a clinically useful measure of aggregate genetic burden and improve patient risk stratification. Objective: To assess whether a PRS improves prediction of POAG onset in patients with ocular hypertension. Design, Setting, and Participants: This was a post hoc analysis of the Ocular Hypertension Treatment Study. Data were collected from 22 US sites with a mean (SD) follow-up of 14.0 (6.9) years. A total of 1636 participants were followed up from February 1994 to December 2008; 1077 participants were enrolled in an ancillary genetics study, of which 1009 met criteria for this analysis. PRS was calculated using summary statistics from the largest cross-ancestry POAG meta-analysis, with weights trained using 8 813 496 variants from 449 186 cross-ancestry participants in the UK Biobank. Data were analyzed from July 2022 to December 2023. Exposures: From February 1994 to June 2002, participants were randomized to either topical intraocular pressure-lowering medication or close observation. After June 2002, both groups received medication. Main Outcomes and Measures: Outcome measures were hazard ratios for POAG onset. Concordance index and time-dependent areas under the receiver operating characteristic curve were used to compare the predictive performance of multivariable Cox proportional hazards models. Results: Of 1009 included participants, 562 (55.7%) were female, and the mean (SD) age was 55.9 (9.3) years. The mean (SD) PRS was significantly higher for 350 POAG converters (0.24 [0.95]) compared with 659 nonconverters (-0.12 [1.00]) (P < .001). POAG risk increased 1.36% (95% CI, 1.08-1.64) with each higher PRS decile, with conversion ranging from 9.52% (95% CI, 7.09-11.95) in the lowest PRS decile to 21.81% (95% CI, 19.37-24.25) in the highest decile. Comparison of low-risk and high-risk PRS tertiles showed a 2.0-fold increase in 20-year POAG risk for participants of European and African ancestries. In the subgroup randomized to delayed treatment, each increase in PRS decile was associated with a 0.52-year (95% CI, 0.01-1.03) decrease in age at diagnosis (P = .047). No significant linear association between PRS and age at POAG diagnosis was present in the early treatment group. Prediction models significantly improved with the addition of PRS as a covariate (C index = 0.77) compared with the Ocular Hypertension Treatment Study baseline model (C index = 0.75) (P < .001). Each 1-SD higher PRS conferred a mean hazard ratio of 1.25 (95% CI, 1.13-1.44) for POAG onset. Conclusions and Relevance: Higher PRS was associated with increased risk for POAG in patients with ocular hypertension. The inclusion of a PRS improved the prediction of POAG onset. Trial Registration: ClinicalTrials.gov Identifier: NCT00000125.

Visual field progression patterns in the ocular hypertension treatment study correspond to vulnerability regions of the disc.

OBJECTIVES: To determine the locations on the 24-2 visual field (VF) testing grid that are most likely to progress in patients with ocular hypertension (OHTN). Based on a structural model of superior and inferior areas of relative vulnerability at the optic disc, we hypothesized that the nasal and paracentral regions are more prone to show a reduction in sensitivity. METHODS: Posthoc analysis of data collected in phases 1 and 2 of the Ocular Hypertension Treatment Study (OHTS). A pointwise analysis was applied to determine the progression patterns in the early and delayed treatment groups. Each group's progression rate and frequency were calculated for each of the 52 locations corresponding to the 24-2 VF strategy, using trend- and event-based analyses, respectively. RESULTS: For the event-based analysis, the events were most commonly found in the nasal and paracentral regions. The same regions, with some modest variation, were found to have the fastest rates of progression (ROP) measured with trend analysis. A similar pattern of progression was observed in both the early and delayed treatment groups. The difference in event rates and ROP between the early and delayed treatment groups was also greatest in the nasal and paracentral regions. CONCLUSIONS: Development of VF loss in ocular hypertensive eyes appears to be consistent with the vulnerability zones previously described in glaucomatous eyes with established VF loss. Ocular hypotensive treatment likely helps to slow the rate of progression in these regions. This suggests that careful monitoring of these locations may be useful.

Machine Learning-Derived Baseline Visual Field Patterns Predict Future Glaucoma Onset in the Ocular Hypertension Treatment Study.

Purpose: The Ocular Hypertension Treatment Study (OHTS) identified risk factors for primary open-angle glaucoma (POAG) in patients with ocular hypertension, including pattern standard deviation (PSD). Archetypal analysis, an unsupervised machine learning method, may offer a more interpretable approach to risk stratification by identifying patterns in baseline visual fields (VFs). Methods: There were 3272 eyes available in the OHTS. Archetypal analysis was applied using 24-2 baseline VFs, and model selection was performed with cross-validation. Decomposition coefficients for archetypes (ATs) were calculated. A penalized Cox proportional hazards model was implemented to select discriminative ATs. The AT model was compared to the OHTS model. Associations were identified between ATs with both POAG onset and VF progression, defined by mean deviation change per year. Results: We selected 8494 baseline VFs. Optimal AT count was 19. The highest prevalence ATs were AT9, AT11, and AT7. The AT-based prediction model had a C-index of 0.75 for POAG onset. Multivariable models demonstrated that a one-interquartile range increase in the AT5 (hazard ratio [HR] = 1.14; 95% confidence interval [CI], 1.04-1.25), AT8 (HR = 1.22; 95% CI, 1.09-1.37), AT15 (HR = 1.26; 95% CI, 1.12-1.41), and AT17 (HR = 1.17; 95% CI, 1.03-1.31) coefficients conferred increased risk of POAG onset. AT5, AT10, and AT14 were significantly associated with rapid VF progression. In a subgroup analysis by high-risk ATs (>95th percentile or <75th percentile coefficients), PSD lost significance as a predictor of POAG in the low-risk group. Conclusions: Baseline VFs, prior to detectable glaucomatous damage, contain occult patterns representing early changes that may increase the risk of POAG onset and VF progression in patients with ocular hypertension. The relationship between PSD and POAG is modified by the presence of high-risk patterns at baseline. An AT-based prediction model for POAG may provide more interpretable glaucoma-specific information in a clinical setting.

Polygenic Risk Score Improves Prediction of Primary Open Angle Glaucoma Onset in the Ocular Hypertension Treatment Study.

Objective or Purpose: Primary open-angle glaucoma (POAG) is a highly heritable disease with 127 identified risk loci. Polygenic risks score (PRS) offers a measure of aggregate genetic burden. In this study, we assess whether PRS improves risk stratification in patients with ocular hypertension. Design: A post-hoc analysis of the Ocular Hypertension Treatment Study (OHTS) data. Setting Participants and/or Controls: 1636 participants were followed from 1994 to 2020 across 22 sites. The PRS was computed for 1009 OHTS participants using summary statistics from largest cross-ancestry POAG metanalysis with weights trained using 8,813,496 variants from 488,395 participants in the UK Biobank. Methods Interventions or Testing: Survival regression analysis, with endpoint as development of POAG, predicted disease onset from PRS incorporating baseline covariates. Main Outcomes and Measures: Outcome measures were hazard ratios for POAG onset. Concordance index and time-dependent AUC were used to compare the predictive performance of multivariable Cox-Proportional Hazards models. Results: Mean PRS was significantly higher for POAG-converters (0.24 ± 0.95) than for non-converters (-0.12 ± 1.00) (p < 0.01). POAG risk increased 1.36% with each higher PRS decile, with conversion ranging from 9.5% in the lowest PRS decile to 21.8% in the highest decile. Comparison of low- and high-risk PRS tertiles showed a 1.8-fold increase in 20-year POAG risk for participants of European and African ancestries (p<0.01). In the subgroup randomized to delayed treatment, each increase in PRS decile was associated with a 0.52-year decrease in age at diagnosis, (p=0.05). No significant linear relationship between PRS and age at POAG diagnosis was present in the early treatment group. Prediction models significantly improved with the addition of PRS as a covariate (C-index = 0.77) compared to OHTS baseline model (C-index=0.75) (p<0.01). One standard deviation higher PRS conferred a mean hazard ratio of 1.25 (CI=[1.13, 1.44]) for POAG onset. Conclusions: Higher PRS is associated with increased risk for, and earlier development of POAG in patients with ocular hypertension. Early treatment may mitigate the risk from high genetic burden, delaying clinically detectable disease by up to 5.2 years. The inclusion of a PRS improves the prediction of POAG onset.

What is the Optimal Frequency of Visual Field Testing to Detect Rapid Progression Among Hypertensive Eyes?

PRCIS: We evaluated 16,351 visual field (VF) tests from Ocular Hypertension Treatment Study (OHTS) database and showed that more frequent testing resulted in a shorter time to detect glaucoma progression, with the best trade-off being the 6-month intervals for high-risk and 12 months for low-risk patients. PURPOSE: To investigate the effect of different testing intervals on time to detect visual field progression in eyes with ocular hypertension. METHODS: A total of 16,351 reliable 30-2 VF tests from 1575 eyes of the OHTS-1 observation arm with a mean (95% CI) follow-up of 4.8 (4.7-4.8) years were analyzed. Computer simulations (n = 10,000 eyes) based on mean deviation values and the residuals of risk groups (according to their baseline 5 y risk of developing primary open angle glaucoma: low, medium, and high risk) were performed to estimate time to detect progression with testing intervals of 4, 6, 12, and 24 months using linear regression. The time to detect VF progression ( P < 5%) at 80% power was calculated based on the mean deviation slope of -0.42 dB/year. We assessed the time to detect a -3 dB loss as an estimate of clinically meaningful perimetric loss. RESULTS: At 80% power, based on the progression of -0.42 dB/year, the best trade-off to detect significant rates of VF change to clinically meaningful perimetric loss in high, medium, and low-risk patients was 6, 6, and 12-month intervals, respectively. CONCLUSION: Given the importance of not missing the conversion to glaucoma, the frequency of testing used in OHTS (6 mo) was optimal for the detection of progression in high-risk patients. Low-risk patients could potentially be tested every 12 months to optimize resource utilization.

Risk Calculation in the Medication Arm of the Ocular Hypertension Treatment Study.

PURPOSE: Risk assessment is integral to the management of individuals with ocular hypertension (OHTN). This study aims to determine the predictive accuracy of the Ocular Hypertension Treatment Study 5-year risk calculator (OHTS calculator) among treated patients with OHTN by applying it to patients randomized to the Ocular Hypertension Treatment Study (OHTS) medication arm. DESIGN: Post hoc secondary analysis of a randomized clinical trial. SUBJECTS: Individuals participating in the OHTS who were randomized to the medication arm. Only participants with complete baseline data in both eyes were included (n = 726). METHODS: The hazard ratios (HRs) of the medication group in OHTS were compared to the HR used for the OHTS calculator using the z-test statistic to establish the OHTS calculator's generalizability to the OHTS medication arm. The performance of the OHTS calculator among the OHTS medication group was evaluated twice, using both untreated baseline intraocular pressure (IOP) and average treated IOP during the first 24 months for the IOP variable. MAIN OUTCOME MEASURES: The performance was determined based on the model's accuracy in estimating the risk of reaching an OHTS primary open-angle glaucoma (POAG) end point using calibration chi-square and discriminating between participants who did or did not develop POAG. RESULTS: The HRs for the OHTS medication arm were not significantly different from those used in the OHTS calculator for untreated OHTN derived from observation arm data (P > 0.1). Based on the calibration chi-square test for the medication group, the OHTS calculator prediction model had good predictive accuracy when using the mean treated IOP and poorer predictive accuracy with the untreated baseline IOP (chi-square 10 and 29, respectively). The model had good discrimination with treated IOP (c-statistic = 0.77), comparable to what has been reported for the OHTS calculator in the OHTS observation group. CONCLUSIONS: The OHTS calculator can be applied to treated patients with OHTN, and repeat risk calculation after initiating IOP reduction may provide useful information that can aid in disease management. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Primary Open-Angle Glaucoma Diagnosis from Optic Disc Photographs Using a Siamese Network.

Purpose: Primary open-angle glaucoma (POAG) is one of the leading causes of irreversible blindness in the United States and worldwide. Although deep learning methods have been proposed to diagnose POAG, these methods all used a single image as input. Contrastingly, glaucoma specialists typically compare the follow-up image with the baseline image to diagnose incident glaucoma. To simulate this process, we proposed a Siamese neural network, POAGNet, to detect POAG from optic disc photographs. Design: The POAGNet, an algorithm for glaucoma diagnosis, is developed using optic disc photographs. Participants: The POAGNet was trained and evaluated on 2 data sets: (1) 37 339 optic disc photographs from 1636 Ocular Hypertension Treatment Study (OHTS) participants and (2) 3684 optic disc photographs from the Sequential fundus Images for Glaucoma (SIG) data set. Gold standard labels were obtained using reading center grades. Methods: We proposed a Siamese network model, POAGNet, to simulate the clinical process of identifying POAG from optic disc photographs. The POAGNet consists of 2 side outputs for deep supervision and uses convolution to measure the similarity between 2 networks. Main Outcome Measures: The main outcome measures are the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity. Results: In POAG diagnosis, extensive experiments show that POAGNet performed better than the best state-of-the-art model on the OHTS test set (area under the curve [AUC] 0.9587 versus 0.8750). It also outperformed the baseline models on the SIG test set (AUC 0.7518 versus 0.6434). To assess the transferability of POAGNet, we also validated the impact of cross-data set variability on our model. The model trained on OHTS achieved an AUC of 0.7490 on SIG, comparable to the previous model trained on the same data set. When using the combination of SIG and OHTS for training, our model achieved superior AUC to the single-data model (AUC 0.8165 versus 0.7518). These demonstrate the relative generalizability of POAGNet. Conclusions: By simulating the clinical grading process, POAGNet demonstrated high accuracy in POAG diagnosis. These results highlight the potential of deep learning to assist and enhance clinical POAG diagnosis. The POAGNet is publicly available on https://github.com/bionlplab/poagnet.

Techno-economic Analysis of Sustainable Biofuels for Marine Transportation.

Renewable, low-carbon biofuels offer the potential opportunity to decarbonize marine transportation. This paper presents a comparative techno-economic analysis and process sustainability assessment of four conversion pathways: (1) hydrothermal liquefaction (HTL) of wet wastes such as sewage sludge and manure; (2) fast pyrolysis of woody biomass; (3) landfill gas Fischer-Tropsch synthesis; and (4) lignin-ethanol oil from the lignocellulosic ethanol biorefinery utilizing reductive catalytic fractionation. These alternative marine biofuels have a modeled minimum fuel selling price between $1.68 and $3.98 per heavy fuel oil gallon equivalent in 2016 U.S. dollars based on a mature plant assessment. The selected pathways also exhibit good process sustainability performance in terms of water intensity compared to the petroleum refineries. Further, the O and S contents of the biofuels vary widely. While the non-HTL biofuels exhibit negligible S content, the raw biocrudes via HTL pathways from sludge and manure show relatively high S contents (>0.5 wt %). Partial or full hydrotreatment can effectively lower the biocrude S content. Additionally, co-feeding with other low-sulfur wet wastes such as food waste can provide another option to produce raw biocrude with lower S content to meet the target with further hydrotreatment. This study indicates that biofuels could be a cost-effective fuel option for the marine sector. Marine biofuels derived from various feedstocks and conversion technologies could mitigate marine biofuel adoption risk in terms of feedstock availability and biorefinery economics.

Automated diagnosing primary open-angle glaucoma from fundus image by simulating human's grading with deep learning.

Primary open-angle glaucoma (POAG) is a leading cause of irreversible blindness worldwide. Although deep learning methods have been proposed to diagnose POAG, it remains challenging to develop a robust and explainable algorithm to automatically facilitate the downstream diagnostic tasks. In this study, we present an automated classification algorithm, GlaucomaNet, to identify POAG using variable fundus photographs from different populations and settings. GlaucomaNet consists of two convolutional neural networks to simulate the human grading process: learning the discriminative features and fusing the features for grading. We evaluated GlaucomaNet on two datasets: Ocular Hypertension Treatment Study (OHTS) participants and the Large-scale Attention-based Glaucoma (LAG) dataset. GlaucomaNet achieved the highest AUC of 0.904 and 0.997 for POAG diagnosis on OHTS and LAG datasets. An ensemble of network architectures further improved diagnostic accuracy. By simulating the human grading process, GlaucomaNet demonstrated high accuracy with increased transparency in POAG diagnosis (comprehensiveness scores of 97% and 36%). These methods also address two well-known challenges in the field: the need for increased image data diversity and relying heavily on perimetry for POAG diagnosis. These results highlight the potential of deep learning to assist and enhance clinical POAG diagnosis. GlaucomaNet is publicly available on https://github.com/bionlplab/GlaucomaNet .

Fabrication of Black Body Grids by Thick Film Printing for Quantitative Neutron Imaging.

Neutron imaging offers deep penetration through many high-Z materials while also having high sensitivity to certain low-Z isotopes such as 1H, 6Li, and 10B. This unique combination of properties has made neutron imaging an attractive tool for a wide range of material science and engineering applications. However, measurements made by neutron imaging or tomography are generally qualitative in nature due to the inability of detectors to discriminate between neutrons which have been transmitted through the sample and neutrons which are scattered by the sample or within the detector. Recent works have demonstrated that deploying a grid of small black bodies (BBs) in front of the sample can allow for the scattered neutrons to be measured at the BB locations and subsequently subtracted from the total measured intensity to yield a quantitative transmission measurement. While this method can be very effective, factors such as the scale and composition of the sample, the beam divergence, and the resolution and construction of the detector may require optimization of the grid design to remove all measurement biases within a given experimental setup. Therefore, it is desirable to have a method by which BB grids may be rapidly and inexpensively produced such that they can easily be tailored to specific applications. In this work, we present a method for fabricating BB patterns by thick film printing of Gd2O3 and evaluate the performance with variation in feature size and number of print layers with cold and thermal neutrons.

Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning.

Importance: Automated deep learning (DL) analyses of fundus photographs potentially can reduce the cost and improve the efficiency of reading center assessment of end points in clinical trials. Objective: To investigate the diagnostic accuracy of DL algorithms trained on fundus photographs from the Ocular Hypertension Treatment Study (OHTS) to detect primary open-angle glaucoma (POAG). Design, Setting, and Participants: In this diagnostic study, 1636 OHTS participants from 22 sites with a mean (range) follow-up of 10.7 (0-14.3) years. A total of 66 715 photographs from 3272 eyes were used to train and test a ResNet-50 model to detect the OHTS Endpoint Committee POAG determination based on optic disc (287 eyes, 3502 photographs) and/or visual field (198 eyes, 2300 visual fields) changes. Three independent test sets were used to evaluate the generalizability of the model. Main Outcomes and Measures: Areas under the receiver operating characteristic curve (AUROC) and sensitivities at fixed specificities were calculated to compare model performance. Evaluation of false-positive rates was used to determine whether the DL model detected POAG before the OHTS Endpoint Committee POAG determination. Results: A total of 1147 participants were included in the training set (661 [57.6%] female; mean age, 57.2 years; 95% CI, 56.6-57.8), 167 in the validation set (97 [58.1%] female; mean age, 57.1 years; 95% CI, 55.6-58.7), and 322 in the test set (173 [53.7%] female; mean age, 57.2 years; 95% CI, 56.1-58.2). The DL model achieved an AUROC of 0.88 (95% CI, 0.82-0.92) for the OHTS Endpoint Committee determination of optic disc or VF changes. For the OHTS end points based on optic disc changes or visual field changes, AUROCs were 0.91 (95% CI, 0.88-0.94) and 0.86 (95% CI, 0.76-0.93), respectively. False-positive rates (at 90% specificity) were higher in photographs of eyes that later developed POAG by disc or visual field (27.5% [56 of 204]) compared with eyes that did not develop POAG (11.4% [50 of 440]) during follow-up. The diagnostic accuracy of the DL model developed on the optic disc end point applied to 3 independent data sets was lower, with AUROCs ranging from 0.74 (95% CI, 0.70-0.77) to 0.79 (95% CI, 0.78-0.81). Conclusions and Relevance: The model's high diagnostic accuracy using OHTS photographs suggests that DL has the potential to standardize and automate POAG determination for clinical trials and management. In addition, the higher false-positive rate in early photographs of eyes that later developed POAG suggests that DL models detected POAG in some eyes earlier than the OHTS Endpoint Committee, reflecting the OHTS design that emphasized a high specificity for POAG determination by requiring a clinically significant change from baseline.

Cataract Surgery Lowers Intraocular Pressure and Medication Use in the Medication Group of the Ocular Hypertension Treatment Study.

PURPOSE: To determine the change in intraocular pressure (IOP) and ocular hypotensive medication use after cataract extraction in the Medication Group of the Ocular Hypertension Treatment Study. DESIGN: Secondary analysis of randomized clinical trial data. METHODS: We included 92 participants (n = 149 eyes) of the Medication Group of the Ocular Hypertension Treatment Study who underwent cataract surgery in at least 1 eye during the study and 531 participants (n = 1004 eyes) of the Medication Group who did not undergo cataract surgery. We defined the "split date" as the first study visit that cataract surgery was reported for the cataract surgery group and the 15th visit in the control group to equalize the median number of visits. We then compared the 2 groups at visits relative to this split date. MAIN OUTCOME MEASURES: Difference in preoperative and postoperative IOP, and number of classes of ocular hypotensive medications between the cataract and control group over a 72-month period. RESULTS: Cataract surgery significantly decreased the number of ocular hypotensive medications at all postoperative visits (mean, -0.4 medications; P ≤ .005) through the 48-month postoperative visit when compared with the control group. At the split date, approximately 23% of eyes were medication free and 41% had a reduced medication burden. Cataract surgery resulted in a decrease in IOP (P < .001), but the difference in IOP between the groups reduced over time and became nonsignificant after 12 months. CONCLUSIONS: Cataract surgery in patients with ocular hypertension produced sustained reductions in the average number of ocular hypotensive medications and transient reductions in IOP.

Multi-scale Multi-structure Siamese Network (MMSNet) for Primary Open-Angle Glaucoma Prediction.

Primary open-angle glaucoma (POAG) is one of the leading causes of irreversible blindness in the United States and worldwide. POAG prediction before onset plays an important role in early treatment. Although deep learning methods have been proposed to predict POAG, these methods mainly focus on current status prediction. In addition, all these methods used a single image as input. On the other hand, glaucoma specialists determine a glaucomatous eye by comparing the follow-up optic nerve image with the baseline along with supplementary clinical data. To simulate this process, we proposed a Multi-scale Multi-structure Siamese Network (MMSNet) to predict future POAG event from fundus photographs. The MMSNet consists of two side-outputs for deep supervision and 2D blocks to utilize two-dimensional features to assist classification. The MMSNet network was trained and evaluated on a large dataset: 37,339 fundus photographs from 1,636 Ocular Hypertension Treatment Study (OHTS) participants. Extensive experiments show that MMSNet outperforms the state-of-the-art on two "POAG prediction before onset" tasks. Our AUC are 0.9312 and 0.9507, which are 0.2204 and 0.1490 higher than the state-of-the-art, respectively. In addition, an ablation study is performed to check the contribution of different components. These results highlight the potential of deep learning to assist and enhance the prediction of future POAG event. The proposed network will be publicly available on https://github.com/bionlplab/MMSNet.

Assessment of Cumulative Incidence and Severity of Primary Open-Angle Glaucoma Among Participants in the Ocular Hypertension Treatment Study After 20 Years of Follow-up.

Importance: Ocular hypertension is an important risk factor for the development of primary open-angle glaucoma (POAG). Data from long-term follow-up can be used to inform the management of patients with ocular hypertension. Objective: To determine the cumulative incidence and severity of POAG after 20 years of follow-up among participants in the Ocular Hypertension Treatment Study. Design, Setting, and Participants: Participants in the Ocular Hypertension Treatment Study were followed up from February 1994 to December 2008 in 22 clinics. Data were collected after 20 years of follow-up (from January 2016 to April 2019) or within 2 years of death. Analyses were performed from July 2019 to December 2020. Interventions: From February 28, 1994, to June 2, 2002 (phase 1), participants were randomized to receive either topical ocular hypotensive medication (medication group) or close observation (observation group). From June 3, 2002, to December 30, 2008 (phase 2), both randomization groups received medication. Beginning in 2009, treatment was no longer determined by study protocol. From January 7, 2016, to April 15, 2019 (phase 3), participants received ophthalmic examinations and visual function assessments. Main Outcomes and Measures: Twenty-year cumulative incidence and severity of POAG in 1 or both eyes after adjustment for exposure time. Results: A total of 1636 individuals (mean [SD] age, 55.4 [9.6] years; 931 women [56.9%]; 1138 White participants [69.6%]; 407 Black/African American participants [24.9%]) were randomized in phase 1 of the clinical trial. Of those, 483 participants (29.5%) developed POAG in 1 or both eyes (unadjusted incidence). After adjusting for exposure time, the 20-year cumulative incidence of POAG in 1 or both eyes was 45.6% (95% CI, 42.3%-48.8%) among all participants, 49.3% (95% CI, 44.5%-53.8%) among participants in the observation group, and 41.9% (95% CI, 37.2%-46.3%) among participants in the medication group. The 20-year cumulative incidence of POAG was 55.2% (95% CI, 47.9%-61.5%) among Black/African American participants and 42.7% (95% CI, 38.9%-46.3%) among participants of other races. The 20-year cumulative incidence for visual field loss was 25.2% (95% CI, 22.5%-27.8%). Using a 5-factor baseline model, the cumulative incidence of POAG among participants in the low-, medium-, and high-risk tertiles was 31.7% (95% CI, 26.4%-36.6%), 47.6% (95% CI, 41.6%-53.0%), and 59.8% (95% CI, 53.1%-65.5%), respectively. Conclusions and Relevance: In this study, only one-fourth of participants in the Ocular Hypertension Treatment Study developed visual field loss in either eye over long-term follow-up. This information, together with a prediction model, may help clinicians and patients make informed personalized decisions about the management of ocular hypertension. Trial Registration: ClinicalTrials.gov Identifier: NCT00000125.

Low-energy Selective Laser Trabeculoplasty Repeated Annually: Rationale for the COAST Trial.

The recent Laser in Glaucoma and Ocular Hypertension Trial provided the evidentiary basis for a paradigm shift away from the historical medication-first approach to glaucoma--which has numerous limitations, the most important of which is poor adherence to therapy --and toward a laser-first approach. Now 20 years after its commercialization, selective laser trabeculoplasty (SLT) is routinely performed consistently with its initial description, with energy titrated to the appearance of fine, champagne-like cavitation bubbles. A recent data set suggested that lower energy SLT, applied as primary therapy and repeated annually irrespective of intraocular pressure--rather than pro re nata when its effect wanes and irrespective of intraocular pressure rises --yields longer medication-free survival than standard energy SLT repeated pro re nata. A new study--Clarifying the Optimal Application of SLT Therapy --has been initiated to explore this preliminary finding in a pair of consecutive randomized trials. Herein, we provide an evidence-based rationale for the use of low-energy SLT repeated annually as primary therapy for mild to moderate primary open-angle glaucoma or high-risk ocular hypertension.

Capturing heterogeneity in repeated measures data by fusion penalty.

In this article, we are interested in capturing heterogeneity in clustered or longitudinal data. Traditionally such heterogeneity is modeled by either fixed effects (FE) or random effects (RE). In FE models, the degree of freedom for the heterogeneity equals the number of clusters/subjects minus 1, which could result in less efficiency. In RE models, the heterogeneity across different clusters/subjects is described by, for example, a random intercept with 1 parameter (for the variance of the random intercept), which could lead to oversimplification and biases (for the estimates of subject-specific effects). Our "fused effects" model stands in between these two approaches: we assume that there are unknown number of distinct levels of heterogeneity, and use the fusion penalty approach for estimation and inference. We evaluate and compare the performance of our method to the FE and RE models by simulation studies. We apply our method to the Ocular Hypertension Treatment Study to capture the heterogeneity in the progression rate of primary open-angle glaucoma of left and right eyes of different subjects.

Evaluation of a Primary Open-Angle Glaucoma Prediction Model Using Long-term Intraocular Pressure Variability Data: A Secondary Analysis of 2 Randomized Clinical Trials.

Importance: The contribution of long-term intraocular pressure (IOP) variability to the development of primary open-angle glaucoma is still controversial. Objective: To assess whether long-term IOP variability data improve a prediction model for the development of primary open-angle glaucoma (POAG) in individuals with untreated ocular hypertension. Design, Setting, and Participants: This post hoc secondary analysis of 2 randomized clinical trials included data from 709 of 819 participants in the observation group of the Ocular Hypertension Treatment Study (OHTS) followed up from February 28, 1994, to June 1, 2002, and 397 of 500 participants in the placebo group of the European Glaucoma Prevention Study (EGPS) followed up from January 1, 1997, to September 30, 2003. Data analyses were completed between January 1, 2019, and March 15, 2020. Exposures: The original prediction model for the development of POAG included the following baseline factors: age, IOP, central corneal thickness, vertical cup-disc ratio, and pattern SD. This analysis tested whether substitution of baseline IOP with mean follow-up IOP, SD of IOP, maximum IOP, range of IOP, or coefficient of variation IOP would improve predictive accuracy. Main Outcomes and Measures: The C statistic was used to compare the predictive accuracy of multivariable landmark Cox proportional hazards regression models for the development of POAG. Results: Data from the OHTS consisted of 97 POAG end points from 709 of 819 participants (416 [58.7%] women; 177 [25.0%] African American and 490 [69.1%] white; mean [SD] age, 55.7 [9.59] years; median [range] follow-up, 6.9 [0.96-8.15] years). Data from the EGPS consisted of 44 POAG end points from 397 of 500 participants in the placebo group (201 [50.1%] women; 397 [100%] white; mean [SD] age, 57.8 [9.76] years; median [range] follow-up, 4.9 [1.45-5.76] years). The C statistic for the original prediction model was 0.741. When a measure of follow-up IOP was substituted for baseline IOP in this prediction model, the C statistics were as follows: mean follow-up IOP, 0.784; maximum IOP, 0.781; SD of IOP, 0.745; range of IOP, 0.741; and coefficient of variation IOP, 0.729. The C statistics in the EGPS were similarly ordered. No measure of IOP variability, when added to the prediction model that included mean follow-up IOP, age, central corneal thickness, vertical cup-disc ratio, and pattern SD, increased the C statistic by more than 0.007 in either cohort. Conclusions and Relevance: Evidence from the OHTS and the EGPS suggests that long-term variability does not add substantial explanatory power to the prediction model as to which individuals with untreated ocular hypertension will develop POAG.

Densitometric Profiles of Optic Disc Hemorrhages in the Ocular Hypertension Treatment Study.

PURPOSE: The origin of blood in glaucoma-related disc hemorrhages (DH) remains unknown. A prior clinic-based study of primary open-angle glaucoma (POAG)-related DH showed that they had grayscale pixel intensities more similar to blood from retinal macroaneurysms and adjacent retinal arterioles than to blood from retinal vein occlusions or adjacent retinal venules, suggesting an arterial source. Here we assessed the densitometric profile of DH from fundus photographs in the Ocular Hypertension Treatment Study (OHTS). DESIGN: Retrospective cross-sectional study of prospectively collected images. METHODS: Stereo disc photographs of 161 DH events from 83 OHTS participants (mean age [standard deviation (SD)]: 65.6 [9.2] years; 46.6% female; 13.0% black race) were imported into ImageJ to measure densitometry differences (adjacent arterioles minus DH [ΔA] or venules minus DH [ΔV]). Their size as percentage of disc area, ratio of length to midpoint width, and location relative to the disc margin were also analyzed. We performed t tests to compare ΔA and ΔV, analysis of variance to compare ΔA and ΔV across DH recurrent events, and multivariable linear regression to identify determinants of ΔA and ΔV. RESULTS: Mean (SD) ΔA and ΔV were -2.2 (8.7) and -11.4 (9.7) pixel intensity units, respectively (P < .001). ΔA and ΔV each did not differ significantly across recurrence of DH (P ≥ .92) or between DH events with and without POAG (P ≥ .26). CONCLUSIONS: OHTS DH had densitometric measurements more similar in magnitude to adjacent arterioles than venules, supporting an arterial origin for DH. Vascular dysregulation may contribute to disc hemorrhage formation in ocular hypertension.

Central Corneal Thickness in the Ocular Hypertension Treatment Study (OHTS).

OBJECTIVE: Central corneal thickness influences intraocular pressure (IOP) measurement. We examined the central corneal thickness of subjects in the Ocular Hypertension Treatment Study (OHTS) and determined if central corneal thickness is related to race. DESIGN: Cross-sectional study. PARTICIPANTS: One thousand three hundred one OHTS subjects with central corneal thickness measurements. INTERVENTION: Central corneal thickness was determined with ultrasonic pachymeters of the same make and model at all clinical sites of the OHTS. MAIN OUTCOME MEASURES: Correlation of mean central corneal thickness with race, baseline IOP, refraction, age, gender, systemic hypertension, and diabetes. RESULTS: Mean central corneal thickness was 573.0 ± 39.0 µm. Twenty-four percent of the OHTS subjects had central corneal thickness > 600 µm. Mean central corneal thickness for African American subjects (555.7 ± 40.0 µm; n = 318) was 23 µm thinner than for white subjects (579.0 ± 37.0 µm; P < 0.0001). Other factors associated with greater mean central corneal thickness were younger age, female gender, and diabetes. CONCLUSIONS: OHTS subjects have thicker corneas than the general population. African American subjects have thinner corneas than white subjects in the study. The effect of central corneal thickness may influence the accuracy of applanation tonometry in the diagnosis, screening, and management of patients with glaucoma and ocular hypertension.