Faricimab for neovascular age-related macular degeneration and diabetic macular edema: from preclinical studies to phase 3 outcomes.

Intravitreal anti-vascular endothelial growth factor (VEGF) therapy is the standard of care for diabetic macular edema (DME) and neovascular age-related macular degeneration (nAMD); however, vision gains and anatomical improvements are not sustained over longer periods of treatment, suggesting other relevant targets may be needed to optimize treatments. Additionally, frequent intravitreal injections can prove a burden for patients and caregivers. Angiopoietin-2 (Ang-2) has been explored as an additional therapeutic target, due to the involvement of Ang-2 in DME and nAMD pathogenesis. Recent evidence supports the hypothesis that targeting both VEGF and Ang-2 may improve clinical outcomes in DME and nAMD compared with targeting VEGF alone by enhancing vascular stability, resulting in reduced macular leakage, prevention of neovascularization, and diminished inflammation. Faricimab, a novel bispecific antibody that targets VEGF-A and Ang-2, has been evaluated in clinical trials for DME (YOSEMITE/RHINE) and nAMD (TENAYA/LUCERNE). These trials evaluated faricimab against the anti-VEGFA/B and anti-placental growth factor fusion protein aflibercept, both administered by intravitreal injection. In addition to faricimab efficacy, safety, and pharmacokinetics, durability was evaluated during the trials using a treat-and-extend regimen. At 1 year, faricimab demonstrated non-inferior vision gains versus aflibercept across YOSEMITE/RHINE and TENAYA/LUCERNE. In YOSEMITE/RHINE, faricimab improved anatomic parameters versus aflibercept. Reduction of central subfield thickness (CST), and absence of both DME and intraretinal fluid were greater in faricimab- versus aflibercept-treated eyes. In TENAYA/LUCERNE, CST reductions were greater for faricimab than aflibercept at the end of the head-to-head phase (0-12 weeks), and were comparable with aflibercept at year 1, but with less frequent dosing. CST and vision gains were maintained during year 2 of both YOSEMITE/RHINE and TENAYA/LUCERNE. These findings suggest that dual Ang-2/VEGF-A pathway inhibition may result in greater disease control versus anti-VEGF alone, potentially addressing the unmet needs and reducing treatment burden, and improving real-world outcomes and compliance in retinal vascular diseases. Long-term extension studies (RHONE-X, AVONELLE-X) are ongoing. Current evidence suggests that dual inhibition with faricimab heralds the beginning of multitargeted treatment strategies inhibiting multiple, independent components of retinal pathology, with faricimab providing opportunities to reduce treatment burden and improve outcomes compared with anti-VEGF monotherapy.

Stereotactic radiotherapy for neovascular age-related macular degeneration (STAR): a pivotal, randomised, double-masked, sham-controlled device trial.

BACKGROUND: Neovascular age-related macular degeneration (nAMD) is a leading cause of blindness. The first-line therapy is anti-vascular endothelial growth factor (anti-VEGF) agents delivered by intravitreal injection. Ionising radiation mitigates key pathogenic processes underlying nAMD, and therefore has therapeutic potential. STAR aimed to assess whether stereotactic radiotherapy (SRT) reduces the number of anti-VEGF injections required, without sacrificing visual acuity. METHODS: This pivotal, randomised, double-masked, sham-controlled trial enrolled participants with pretreated chronic active nAMD from 30 UK hospitals. Participants were randomly allocated in a 2:1 ratio to 16-Gray (Gy) SRT delivered using a robotically controlled device or sham SRT, stratified by treatment centre. Eligible participants were aged 50 years or older and had chronic active nAMD, with at least three previous anti-VEGF injections, including at least one in the last 4 months. Participants and all trial and image reading centre staff were masked to treatment allocation, except one unmasked statistician. The primary outcome was the number of intravitreal ranibizumab injections required over 2 years, tested for superiority (fewer injections). The main secondary outcome was Early Treatment Diabetic Retinopathy Study visual acuity at two years, tested for non-inferiority (five-letter margin). The primary analysis used the intention-to-treat principle, and safety was analysed per-protocol on participants with available data. The study is registered with ClinicalTrials.gov (NCT02243878) and is closed for recruitment. FINDINGS: 411 participants enrolled between Jan 1, 2015, and Dec 27, 2019, and 274 were randomly allocated to the 16-Gy SRT group and 137 to the sham SRT group. 240 (58%) of all participants were female, and 171 (42%) of all participants were male. 241 participants in the 16-Gy SRT group and 118 participants in the sham group were included in the final analysis, and 409 patients were treated and formed the safety population, of whom two patients allocated to sham treatment erroneously received 16-Gy SRT. The SRT group received a mean of 10·7 injections (SD 6·3) over 2 years versus 13·3 injections (5·8) with sham, a reduction of 2·9 injections after adjusting for treatment centre (95% CI -4·2 to -1·6, p<0·0001). The SRT group best-corrected visual acuity change was non-inferior to sham (adjusted mean letter loss difference between groups, -1·7 letters [95% CI -4·2 to 0·8]). Adverse event rates were similar across groups, but reading centre-detected microvascular abnormalities occurred in 77 SRT-treated eyes (35%) and 13 (12%) sham-treated eyes. Overall, eyes with microvascular abnormalities tended to have better best-corrected visual acuity than those without. Fewer ranibizumab injections offset the cost of SRT, saving a mean of £565 per participant (95% CI -332 to 1483). INTERPRETATION: SRT can reduce ranibizumab treatment burden without compromising vision. FUNDING: Medical Research Council and National Institute for Health and Care Research Efficacy and Mechanism Evaluation Programme.

Study protocol: optical coherence tomography angiography for the detection of neovascular age-related macular degeneration: a comprehensive multicentre diagnostic accuracy study in the UK-the ATHENA study.

INTRODUCTION: The diagnosis of neovascular age-related macular degeneration (nAMD), the leading cause of visual impairment in the developed world, relies on the interpretation of various imaging tests of the retina. These include invasive angiographic methods, such as Fundus Fluorescein Angiography (FFA) and, on occasion, Indocyanine-Green Angiography (ICGA). Newer, non-invasive imaging modalities, predominately Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), have drastically transformed the diagnostic approach to nAMD. The aim of this study is to undertake a comprehensive diagnostic accuracy assessment of the various imaging modalities used in clinical practice for the diagnosis of nAMD (OCT, OCTA, FFA and, when a variant of nAMD called Polypoidal Choroidal Vasculopathy is suspected, ICGA) both alone and in various combinations. METHODS AND ANALYSIS: This is a non-inferiority, prospective, randomised diagnostic accuracy study of 1067 participants. Participants are patients with clinical features consistent with nAMD who present to a National Health Service secondary care ophthalmology unit in the UK. Patients will undergo OCT as per standard practice and those with suspicious features of nAMD on OCT will be approached for participation in the study. Patients who agree to take part will also undergo both OCTA and FFA (and ICGA if indicated). Interpretation of the imaging tests will be undertaken by clinicians at recruitment sites. A randomised design was selected to avoid bias from consecutive review of all imaging tests by the same clinician. The primary outcome of the study will be the difference in sensitivity and specificity between OCT+OCTA and OCT+FFA (±ICGA) for nAMD detection as interpreted by clinicians at recruitment sites. ETHICS AND DISSEMINATION: The study has been approved by the South Central-Oxford B Research Ethics Committee with reference number 21/SC/0412.Dissemination of study results will involve peer-review publications, presentations at major national and international scientific conferences. TRIAL REGISTRATION NUMBER: ISRCTN18313457.

Multi-granularity learning of explicit geometric constraint and contrast for label-efficient medical image segmentation and differentiable clinical function assessment.

Automated segmentation is a challenging task in medical image analysis that usually requires a large amount of manually labeled data. However, most current supervised learning based algorithms suffer from insufficient manual annotations, posing a significant difficulty for accurate and robust segmentation. In addition, most current semi-supervised methods lack explicit representations of geometric structure and semantic information, restricting segmentation accuracy. In this work, we propose a hybrid framework to learn polygon vertices, region masks, and their boundaries in a weakly/semi-supervised manner that significantly advances geometric and semantic representations. Firstly, we propose multi-granularity learning of explicit geometric structure constraints via polygon vertices (PolyV) and pixel-wise region (PixelR) segmentation masks in a semi-supervised manner. Secondly, we propose eliminating boundary ambiguity by using an explicit contrastive objective to learn a discriminative feature space of boundary contours at the pixel level with limited annotations. Thirdly, we exploit the task-specific clinical domain knowledge to differentiate the clinical function assessment end-to-end. The ground truth of clinical function assessment, on the other hand, can serve as auxiliary weak supervision for PolyV and PixelR learning. We evaluate the proposed framework on two tasks, including optic disc (OD) and cup (OC) segmentation along with vertical cup-to-disc ratio (vCDR) estimation in fundus images; left ventricle (LV) segmentation at end-diastolic and end-systolic frames along with ejection fraction (LVEF) estimation in two-dimensional echocardiography images. Experiments on nine large-scale datasets of the two tasks under different label settings demonstrate our model's superior performance on segmentation and clinical function assessment.

Glucagon-like Peptide 1 Receptor Agonist use and the effect on diabetic retinopathy: An uncertain relationship.

Glucagon-like Peptide 1 Receptor Agonists (GLP-1 RAs) are a group of relatively novel medications for the treatment of diabetes mellitus. These medications can mimic the naturally occurring incretins of the body, which promote the release of insulin in response to hyperglycaemia. The anti-glycaemic effects of these medications can be profound and carry other metabolic benefits such as promoting weight loss. Clinical trials have shown GLP-1 RAs are safe to use from a cardiovascular perspective. However, some trials have suggested a link between GLP-1 RA use and worsening diabetic retinopathy. The conclusions surrounding this link are poorly established as data is drawn primarily from cardiovascular outcome trials. If an association does exist, a possible explanation might be the observed phenomenon of early worsening diabetic retinopathy with rapid correction of hyperglycaemic states. Trials which look at diabetic retinopathy as a primary outcome in relation to use of GLP-1 RAs are sparse and warrant investigation given the growing use of this group of medications. Therefore currently, it is uncertain what effect, beneficial or adverse, GLP-1 RA use has on diabetic retinopathy. This article provides an overview of GLP-1 RA use as a treatment for diabetes mellitus and the current understanding of their relationship with diabetic retinopathy.

Patient Experience Survey of Anti-Vascular Endothelial Growth Factor Treatment for Neovascular Age-Related Macular Degeneration and Diabetic Macular Edema.

INTRODUCTION: Understanding patient perspectives of treatment may improve adherence and outcomes. This study explored real-world patient experiences with anti-vascular endothelial growth factor (anti-VEGF) treatment for diabetic macular edema (DME) and neovascular age-related macular degeneration (nAMD). METHODS: This multinational, non-interventional, quantitative, cross-sectional, observational survey assessed treatment barriers/burden, patient-reported visual functioning, and treatment satisfaction in DME and nAMD patients in the USA, the UK, Canada, France, Italy, and Spain. Treatment patterns and visual outcomes were extracted from medical charts. Regression models evaluated relationships between adherence, total missed visits, number of anti-VEGF injections, and clinical and patient-reported outcomes for visual functioning. Association between treatment satisfaction and aspects of burden were assessed. RESULTS: The survey was completed by 183 DME and 391 nAMD patients. Patients had moderately high vision-related functioning (25-item National Eye Institute Visual Functioning Questionnaire score: mean = 74.8) and were satisfied with their current treatment (mean total score: Macular Disease Treatment Satisfaction Questionnaire = 59.2; Retinopathy Treatment Satisfaction Questionnaire = 61.3). Treatment satisfaction scores were worse with higher time-related impacts of treatment (nAMD/DME), higher impacts on finances and daily life (nAMD), negative impacts on employment and lower expectations for treatment effectiveness (DME). Most patients reported ≥1 barrier (66.1% DME, 49.2% nAMD patients) related to treatment (35.0%), clinic (32.6%), and COVID-19 (21.1%). Moreover, 44.9% of patients reported some impairment in activities of daily living. Work absenteeism was observed among >60% of working patients. Nearly one-quarter (24.2%) of patients needed ≥1 day to recover from intravitreal injections; most reported ≥30 min of travel time (73.7%) and clinic wait time (54.2%). In unadjusted univariable analyses, treatment adherence (vs. nonadherence) was related to higher most recent visual acuity (ß = 8.98 letters; CI, 1.34-16.62) and lower odds of visual acuity below driving vision (≤69 letters) (OR = 0.50; CI, 0.25-1.00). CONCLUSION: More durable treatments with reduced frequency of injections/visits may reduce treatment burden and improve patient satisfaction, which may enhance adherence and visual outcomes.

Home-Monitoring Vision Tests to Detect Active Neovascular Age-Related Macular Degeneration.

Importance: Most neovascular age-related macular degeneration (nAMD) treatments involve long-term follow-up of disease activity. Home-monitoring would reduce the burden on patients and their caregivers and release clinic capacity. Objective: To evaluate 3 vision home-monitoring tests for patients to use to detect active nAMD compared with diagnosing active nAMD at hospital follow-up during the after-treatment monitoring phase. Design, Setting, and Participants: This was a diagnostic test accuracy study wherein the reference standard was detection of active nAMD by an ophthalmologist at hospital follow-up. The 3 home-monitoring tests evaluated included the following: (1) the KeepSight Journal (KSJ [International Macular and Retinal Foundation]), which contains paper-based near-vision tests presented as word puzzles, (2) the MyVisionTrack (mVT [Genentech]) vision-monitoring mobile app, viewed on an Apple mobile operating system-based device, and (3) the MultiBit (MBT [Visumetrics]) app, viewed on an Apple mobile operating system-based device. Participants were asked to test weekly; mVT and MBT scores were transmitted automatically, and KSJ scores were returned to the research office every 6 months. Raw scores between hospital follow-ups were summarized as averages. Patients were recruited from 6 UK hospital eye clinics and were 50 years and older with at least 1 eye first treated for active nAMD for at least 6 months or longer to a maximum of 42 months before approach. Participants were stratified by time since starting treatment. Study data were analyzed from May to September 2021. Exposures: The KSJ, mVT, and MBT were compared with the reference standard (in-hospital ophthalmologist examination). Main Outcomes and Measures: Estimated area under receiver operating characteristic curve (AUROC). The study had 90% power to detect a difference of 0.06, or 80% power to detect a difference of 0.05, if the AUROC for 2 tests was 0.75. Results: A total of 297 patients (mean [SD] age, 74.9 [6.6] years; 174 female [58.6%]) were included in the study. At least 1 hospital follow-up was available for 312 study eyes in 259 participants (1549 complete visits). Median (IQR) home-monitoring testing frequency was 3 (1-4) times per month. Estimated AUROC was less than 0.6 for all home-monitoring tests, and only the KSJ summary score was associated with lesion activity (odds ratio, 3.48; 95% CI, 1.09-11.13; P = .04). Conclusions and Relevance: Results suggest that no home-monitoring vision test evaluated provided satisfactory diagnostic accuracy to identify active nAMD diagnosed in hospital eye service follow-up clinics. Implementing any of these evaluated tests, with ophthalmologists only reviewing test positives, would mean most active lesions were missed, risking unnecessary sight loss.

Anti-Vascular Endothelial Growth Factor Drugs Compared With Panretinal Photocoagulation for the Treatment of Proliferative Diabetic Retinopathy: A Cost-Effectiveness Analysis.

OBJECTIVES: This study aimed to evaluate the cost-effectiveness of anti-vascular endothelial growth factor drugs (anti-VEGFs) compared with panretinal photocoagulation (PRP) for treating proliferative diabetic retinopathy (PDR) in the United Kingdom. METHODS: A discrete event simulation model was developed, informed by individual participant data meta-analysis. The model captures treatment effects on best corrected visual acuity in both eyes, and the occurrence of diabetic macular edema and vitreous hemorrhage. The model also estimates the value of undertaking further research to resolve decision uncertainty. RESULTS: Anti-VEGFs are unlikely to generate clinically meaningful benefits over PRP. The model predicted anti-VEGFs be more costly and similarly effective as PRP, generating 0.029 fewer quality-adjusted life-years at an additional cost of £3688, with a net health benefit of -0.214 at a £20 000 willingness-to-pay threshold. Scenario analysis results suggest that only under very select conditions may anti-VEGFs offer potential for cost-effective treatment of PDR. The consequences of loss to follow-up were an important driver of model outcomes. CONCLUSIONS: Anti-VEGFs are unlikely to be a cost-effective treatment for early PDR compared with PRP. Anti-VEGFs are generally associated with higher costs and similar health outcomes across various scenarios. Although anti-VEGFs were associated with lower diabetic macular edema rates, the number of cases avoided is insufficient to offset the additional treatment costs. Key uncertainties relate to the long-term comparative effectiveness of anti-VEGFs, particularly considering the real-world rates and consequences of treatment nonadherence. Further research on long-term visual acuity and rates of vision-threatening complications may be beneficial in resolving uncertainties.

Inequalities in Uptake and Use of Digital Applications for Home-Monitoring of Neovascular Age-Related Macular Degeneration in an Elderly Visually Impaired Population: The MONARCH Study.

Purpose: To describe inequalities in the Monitoring for Neovascular Age-related Macular Degeneration Reactivation at Home (MONARCH) diagnostic test accuracy study for: recruitment; participants' ability to self-test; and adherence to testing using digital applications during follow-up. Methods: Home-monitoring vision tests included two tests implemented as software applications (apps: MyVisionTrack and MultiBit) on an iPod Touch device. Patients were provided with all hardware required to participate (iPod and MIFI device) and trained to use the apps. Regression models estimated associations of age, sex, Index of Multiple Deprivation, strata of time since first diagnosis, and baseline visual acuity at study entry on outcomes of willingness to participate, ability to perform tests, and adherence to weekly testing. Results: A minority of patients who were approached were willing-in-principle to participate. Increasing age was associated with being unwilling-in-principle to participate. Patients from the most deprived areas had a 47% decrease in odds of being willing compared to those from the middle quintile deprived areas (odds ratio, 0.53; 95% confidence interval = 0.32, 0.88). Increasing age and worse deprivation were not consistently associated either with ability to self-monitor with the index tests, or adherence to weekly testing. Conclusions: Associations of increasing age and worse deprivation index were associated with unwillingness-in-principle to participate despite the provision of hardware' highlighting the potential for inequality with interventions of the kind evaluated. Translational Relevance: The clear evidence of inequalities in participation should prompt future research on ways to encourage adoption of mobile health technologies by underserved populations.

Descriptive study of the challenges when implementing an app for patients with neovascular age-related macular degeneration to monitor their vision at home.

OBJECTIVES: Remote monitoring of health has the potential to reduce the burden to patients of face-to-face appointments and make healthcare more efficient. Apps are available for patients to self-monitor vision at home, for example, to detect reactivation of age-related macular degeneration (AMD). Describing the challenges when implementing apps for self-monitoring of vision at home was an objective of the MONARCH study to evaluate two vision-monitoring apps on an iPod Touch (Multibit and MyVisionTrack). DESIGN: Diagnostic Test Accuracy study. SETTING: Six UK hospitals. METHODS: The study provides an example of the real-world implementation of such apps across health sectors in an older population. Challenges described include the following: (1) frequency and reason for incoming calls made to a helpline and outgoing calls made to participants; (2) frequency and duration of events responsible for the tests being unavailable; and (3) other technical and logistical challenges. RESULTS: Patients (n=297) in the study were familiar with technology; 252/296 (85%) had internet at home and 197/296 (67%) had used a smartphone. Nevertheless, 141 (46%) called the study helpline, more often than anticipated. Of 435 reasons for calling, all but 42 (10%) related to testing with the apps or hardware, which contributed to reduced adherence. The team made at least one call to 133 patients (44%) to investigate why data had not been transmitted. Multibit and MyVisionTrack apps were unavailable for 15 and 30 of 1318 testing days for reasons which were the responsibility of the app providers. Researchers also experienced technical challenges with a multiple device management system. Logistical challenges included regulations for transporting lithium-ion batteries and malfunctioning chargers. CONCLUSIONS: Implementation of similar technologies should incorporate a well-resourced helpline and build in additional training time for participants and troubleshooting time for staff. There should also be robust evidence that chosen technologies are fit for the intended purpose. TRIAL REGISTRATION NUMBER: ISRCTN79058224.

Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program.

Purpose: To evaluate mydriatic handheld retinal imaging performance assessed by point-of-care (POC) artificial intelligence (AI) as compared with retinal image graders at a centralized reading center (RC) in identifying diabetic retinopathy (DR) and diabetic macular edema (DME). Design: Prospective, comparative study. Subjects: Five thousand five hundred eighty-five eyes from 2793 adult patients with diabetes. Methods: Point-of-care AI assessment of disc and macular handheld retinal images was compared with RC evaluation of validated 5-field handheld retinal images (disc, macula, superior, inferior, and temporal) in identifying referable DR (refDR; defined as moderate nonproliferative DR [NPDR], or worse, or any level of DME) and vision-threatening DR (vtDR; defined as severe NPDR or worse, or any level of center-involving DME [ciDME]). Reading center evaluation of the 5-field images followed the international DR/DME classification. Sensitivity (SN) and specificity (SP) for ungradable images, refDR, and vtDR were calculated. Main Outcome Measures: Agreement for DR and DME; SN and SP for refDR, vtDR, and ungradable images. Results: Diabetic retinopathy severity by RC evaluation: no DR, 67.3%; mild NPDR, 9.7%; moderate NPDR, 8.6%; severe NPDR, 4.8%; proliferative DR, 3.8%; and ungradable, 5.8%. Diabetic macular edema severity by RC evaluation was as follows: no DME (80.4%), non-ciDME (7.7%), ciDME (4.4%), and ungradable (7.5%). Referable DR was present in 25.3% and vtDR was present in 17.5% of eyes. Images were ungradable for DR or DME in 7.5% by RC evaluation and 15.4% by AI. There was substantial agreement between AI and RC for refDR (κ = 0.66) and moderate agreement for vtDR (κ = 0.54). The SN/SP of AI grading compared with RC evaluation was 0.86/0.86 for refDR and 0.92/0.80 for vtDR. Conclusions: This study demonstrates that POC AI following a defined handheld retinal imaging protocol at the time of imaging has SN and SP for refDR that meets the current United States Food and Drug Administration thresholds of 85% and 82.5%, but not for vtDR. Integrating AI at the POC could substantially reduce centralized RC burden and speed information delivery to the patient, allowing more prompt eye care referral. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Automated Machine Learning for Predicting Diabetic Retinopathy Progression From Ultra-Widefield Retinal Images.

Importance: Machine learning (ML) algorithms have the potential to identify eyes with early diabetic retinopathy (DR) at increased risk for disease progression. Objective: To create and validate automated ML models (autoML) for DR progression from ultra-widefield (UWF) retinal images. Design, Setting and Participants: Deidentified UWF images with mild or moderate nonproliferative DR (NPDR) with 3 years of longitudinal follow-up retinal imaging or evidence of progression within 3 years were used to develop automated ML models for predicting DR progression in UWF images. All images were collected from a tertiary diabetes-specific medical center retinal image dataset. Data were collected from July to September 2022. Exposure: Automated ML models were generated from baseline on-axis 200° UWF retinal images. Baseline retinal images were labeled for progression based on centralized reading center evaluation of baseline and follow-up images according to the clinical Early Treatment Diabetic Retinopathy Study severity scale. Images for model development were split 8-1-1 for training, optimization, and testing to detect 1 or more steps of DR progression. Validation was performed using a 328-image set from the same patient population not used in model development. Main Outcomes and Measures: Area under the precision-recall curve (AUPRC), sensitivity, specificity, and accuracy. Results: A total of 1179 deidentified UWF images with mild (380 [32.2%]) or moderate (799 [67.8%]) NPDR were included. DR progression was present in half of the training set (590 of 1179 [50.0%]). The model's AUPRC was 0.717 for baseline mild NPDR and 0.863 for moderate NPDR. On the validation set for eyes with mild NPDR, sensitivity was 0.72 (95% CI, 0.57-0.83), specificity was 0.63 (95% CI, 0.57-0.69), prevalence was 0.15 (95% CI, 0.12-0.20), and accuracy was 64.3%; for eyes with moderate NPDR, sensitivity was 0.80 (95% CI, 0.70-0.87), specificity was 0.72 (95% CI, 0.66-0.76), prevalence was 0.22 (95% CI, 0.19-0.27), and accuracy was 73.8%. In the validation set, 6 of 9 eyes (75%) with mild NPDR and 35 of 41 eyes (85%) with moderate NPDR progressed 2 steps or more were identified. All 4 eyes with mild NPDR that progressed within 6 months and 1 year were identified, and 8 of 9 (89%) and 17 of 20 (85%) with moderate NPDR that progressed within 6 months and 1 year, respectively, were identified. Conclusions and Relevance: This study demonstrates the accuracy and feasibility of automated ML models for identifying DR progression developed using UWF images, especially for prediction of 2-step or greater DR progression within 1 year. Potentially, the use of ML algorithms may refine the risk of disease progression and identify those at highest short-term risk, thus reducing costs and improving vision-related outcomes.

Diabetic Retinopathy and Quality of Life: A Systematic Review and Meta-Analysis.

Importance: The association between diabetic retinopathy (DR) and quality of life (QoL) has not been thoroughly investigated. Objective: To investigate the association between DR and both vision-related QoL (VRQoL) and general health-related QoL (HRQoL). Data Sources: MEDLINE, EBSCO, Embase, and Web of Science were searched from their inception to April 2022. Study Selection: Studies included adults with DR and a measure of QoL. Data Extraction and Synthesis: Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Two assumption-free meta-analyses were conducted. Analysis 1 included studies with participants without DR as the referent group to which QoL scores of participants with DR, grouped according to DR severity, were compared. Analysis 2 included all studies with participants with DR and a measure of QoL. QoL scores were pooled within categories of DR severity, and comparisons were made between these categories. Main Outcome and Measures: QoL measured using HRQoL and VRQoL scales. Results: A total of 93 articles were included: 79 in the meta-analyses and 14 in the narrative results. VRQoL was recorded in 54 studies, HRQoL in 26, and both in 13 studies. The most commonly used scales were the National Eye Institute 25-item Visual Function Questionnaire (VFQ-25) (n = 49) for VRQoL and the Short Form (SF) Health Survey (n = 18) for HRQoL. Thirty-five studies reported VFQ-25 composite scores. Analysis 1 consisted of 8 studies including 1138 participants with DR and 347 participants without DR. Compared with participants without DR, the composite VFQ-25 score was 3.8 (95% CI, 1.0-6.7) points lower in those with non-vision-threatening DR (NVTDR), 12.5 (95% CI, 8.5-16.5) lower in those with any DR, and 25.1 (95% CI, 22.8-27.2) lower in VTDR (P < .001 for trend). Analysis 2 consisted of 35 studies including 6351 participants with DR. The pooled mean VFQ-25 composite score was 91.8 (95% CI, 91.0-92.7) for participants with NVTDR, 77.6 (95% CI, 76.9-78.3) for any DR, and 73.2 (95% CI, 72.6-73.7) for VTDR (P < .001 for trend). HRQoL scores had weak or no associations with NVTDR and strong associations with VTDR. Conclusions and Relevance: This study found that VRQoL declined with the presence and severity of DR. Interventions to reduce progression of DR at both early and more advanced stages could improve VRQoL.

Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2.

Importance: Deep learning image analysis often depends on large, labeled datasets, which are difficult to obtain for rare diseases. Objective: To develop a self-supervised approach for automated classification of macular telangiectasia type 2 (MacTel) on optical coherence tomography (OCT) with limited labeled data. Design, Setting, and Participants: This was a retrospective comparative study. OCT images from May 2014 to May 2019 were collected by the Lowy Medical Research Institute, La Jolla, California, and the University of Washington, Seattle, from January 2016 to October 2022. Clinical diagnoses of patients with and without MacTel were confirmed by retina specialists. Data were analyzed from January to September 2023. Exposures: Two convolutional neural networks were pretrained using the Bootstrap Your Own Latent algorithm on unlabeled training data and fine-tuned with labeled training data to predict MacTel (self-supervised method). ResNet18 and ResNet50 models were also trained using all labeled data (supervised method). Main Outcomes and Measures: The ground truth yes vs no MacTel diagnosis is determined by retinal specialists based on spectral-domain OCT. The models' predictions were compared against human graders using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under precision recall curve (AUPRC), and area under the receiver operating characteristic curve (AUROC). Uniform manifold approximation and projection was performed for dimension reduction and GradCAM visualizations for supervised and self-supervised methods. Results: A total of 2636 OCT scans from 780 patients with MacTel and 131 patients without MacTel were included from the MacTel Project (mean [SD] age, 60.8 [11.7] years; 63.8% female), and another 2564 from 1769 patients without MacTel from the University of Washington (mean [SD] age, 61.2 [18.1] years; 53.4% female). The self-supervised approach fine-tuned on 100% of the labeled training data with ResNet50 as the feature extractor performed the best, achieving an AUPRC of 0.971 (95% CI, 0.969-0.972), an AUROC of 0.970 (95% CI, 0.970-0.973), accuracy of 0.898%, sensitivity of 0.898, specificity of 0.949, PPV of 0.935, and NPV of 0.919. With only 419 OCT volumes (185 MacTel patients in 10% of labeled training dataset), the ResNet18 self-supervised model achieved comparable performance, with an AUPRC of 0.958 (95% CI, 0.957-0.960), an AUROC of 0.966 (95% CI, 0.964-0.967), and accuracy, sensitivity, specificity, PPV, and NPV of 90.2%, 0.884, 0.916, 0.896, and 0.906, respectively. The self-supervised models showed better agreement with the more experienced human expert graders. Conclusions and Relevance: The findings suggest that self-supervised learning may improve the accuracy of automated MacTel vs non-MacTel binary classification on OCT with limited labeled training data, and these approaches may be applicable to other rare diseases, although further research is warranted.

Macula vs periphery in diabetic retinopathy: OCT-angiography and ultrawide field fluorescein angiography imaging of retinal non perfusion.

OBJECTIVES: To investigate the association between peripheral non-perfusion index (NPI) on ultrawide-field fluorescein angiography (UWF-FA) and quantitative OCT-Angiography (OCT-A) metrics in the macula. METHODS: In total, 48 eyes with UWF-colour fundus photos (CFP), UWF-FA (California, Optos) and OCT-A (Spectralis, Heidelberg) were included. OCT-A (3 × 3 mm) was used to determine foveal avascular zone (FAZ) parameters and vessel density (VD), perfusion density (PD), fractal dimension (FD) on superficial capillary plexus (SCP). NPI's extent and distribution was determined on UWF-FA within fovea centred concentric rings corresponding to posterior pole (<10 mm), mid-periphery (10-15 mm), and far-periphery (>15 mm) and within the total retinal area, the central macular field (6×6 mm), ETDRS fields and within each extended ETDRS field (P3-P7). RESULTS: Macular PD was correlated to NPI in total area of retina (Spearman ρ = 0.69, p < 0.05), posterior pole (ρ = 0.48, p < 0.05), mid-periphery (ρ = 0.65, p < 0.05), far-periphery (ρ = 0.59, p < 0.05), P3-P7 (ρ = 0,55 at least, p < 0.05 for each), central macula (ρ = 0.47, p < 0.05), total area in ETDRS (ρ = 0.55, p < 0.05). Macular VD and FD were correlated to NPI of total area of the retina (ρ = 0.60 and 0.61, p < 0.05), the mid-periphery (ρ = 0.56, p < 0.05) and far-periphery (ρ = 0.60 and ρ = 0.61, p < 0.05), and in P3-P7 (p < 0.05). FAZ perimeter was significantly corelated to NPI at posterior pole and central macular area (ρ = 0.37 and 0.36, p < 0.05), and FAZ area to NPI in central macular area (ρ = 0.36, p < 0.05). CONCLUSIONS: Perfusion macular metrics on OCT-A correlated with UWF-FA's non-perfusion (NP), particularly in the retina's mid and far periphery, suggesting that OCT-A might be a useful non-invasive method to estimate peripheral retinal NP.

Adalimumab vs placebo as add-on to Standard Therapy for autoimmune Uveitis: Tolerability, Effectiveness and cost-effectiveness-a protocol for a randomised controlled trial (ASTUTE trial).

INTRODUCTION: Adalimumab is an effective treatment for autoimmune non-infectious uveitis (ANIU), but it is currently only funded for a minority of patients with ANIU in the UK as it is restricted by the National Institute for Health and Care Excellence guidance. Ophthalmologists believe that adalimumab may be effective in a wider range of patients. The Adalimumab vs placebo as add-on to Standard Therapy for autoimmune Uveitis: Tolerability, Effectiveness and cost-effectiveness (ASTUTE) trial will recruit patients with ANIU who do and do not meet funding criteria and will evaluate the effectiveness and cost-effectiveness of adalimumab versus placebo as an add-on therapy to standard care. METHODS AND ANALYSIS: The ASTUTE trial is a multicentre, parallel-group, placebo-controlled, pragmatic randomised controlled trial with a 16-week treatment run-in (TRI). At the end of the TRI, only responders will be randomised (1:1) to 40 mg adalimumab or placebo (both are the study investigational medicinal product) self-administered fortnightly by subcutaneous injection. The target sample size is 174 randomised participants. The primary outcome is time to treatment failure (TF), a composite of signs indicative of active ANIU. Secondary outcomes include individual TF components, retinal morphology, adverse events, health-related quality of life, patient-reported side effects and visual function, best-corrected visual acuity, employment status and resource use. In the event of TF, open-label drug treatment will be restarted as per TRI for 16 weeks, and if a participant responds again, allocation will be switched without unmasking and treatment with investigational medicinal product restarted. ETHICS AND DISSEMINATION: The trial received Research Ethics Committee (REC) approval from South Central - Oxford B REC in June 2020. The findings will be presented at international meetings, by peer-reviewed publications and through patient organisations and newsletters to patients, where available. TRIAL REGISTRATION: ISRCTN31474800. Registered 14 April 2020.

Improved Structure and Function in Early-Detected Second-Eye Neovascular Age-Related Macular Degeneration: FASBAT/Early Detection of Neovascular Age-Related Macular Degeneration Report 1.

PURPOSE: Visual acuity (VA) and structural biomarker assessment before and 24-months after early detection and routine treatment of second-eye involvement with neovascular age-related macular degeneration (nAMD) and additional comparison with the first eye affected. DESIGN: Prospective, 22-center observational study of participants with unilateral nAMD in the Early Detection of Neovascular AMD (EDNA) study, coenrolled into the Observing Fibrosis, Macular Atrophy and Subretinal Highly Reflective Material, Before and After Intervention with anti-VEGF Treatment (FASBAT) study for an additional 2-year follow-up. PARTICIPANTS: Older adults (> 50 years) with new onset nAMD in the first eye. METHODS: Assessment of both eyes with OCT, color fundus photography (CFP), clinic-measured VA, and quality of life (QoL). MAIN OUTCOME MEASURES: Prevalence of atrophy, subretinal hyperreflective material (SHRM), intraretinal fluid (IRF), subretinal fluid (SRF), and changes in VA over the study duration in both the first and second eyes affected with nAMD. Composite QoL scores over time. RESULTS: Of 431 participants recruited to the FASBAT study, the second eye converted to nAMD in 100 participants at a mean of 18.9 months. Visual acuity was 18 letters better at the time of early diagnosis in the second eye compared with conventional diagnosis in the first eye (72.9 vs. 55.6 letters). Visual acuity remained better in the second eye 24.9 months postconversion, at 69.5 letters compared with 59.7 letters at a similar matched time point in the first eye (18.9 months). A greater proportion of participants had vision > 70 letters in the second eye versus the first eye, 24.9 months postconversion (61 vs. 35). Prevalence of SHRM and IRF was lower in the second eye compared with the first eye 24.9 months postconversion. However, SRF prevalence was greater in the second eye 24.9 months postconversion. The development and progression of total area of atrophy appears similar in both eyes. Mean composite QoL scores increased over time, with a significant correlation between VA for the second eye only 24.9 months postconversion. CONCLUSION: This study has shown that early detection of exudative AMD in the second eye is associated with reduced prevalence of SHRM and IRF and greater VA, which is significantly correlated with maintained QoL. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Self-reported dual sensory impairment and related factors: a European population-based cross-sectional survey.

BACKGROUND: Data on population-based self-reported dual vision and hearing impairment are sparse in Europe. We aimed to investigate self-reported dual sensory impairment (DSI) in European population. METHODS: A standardised questionnaire was used to collect medical and socio-economic data among individuals aged 15 years or more in 29 European countries. Individuals living in collective households or in institutions were excluded from the survey. RESULTS: Among 296 677 individuals, the survey included 153 866 respondents aged 50 years old or more. The crude prevalence of DSI was of 7.54% (7.36-7.72). Among individuals aged 60 or more, 9.23% of men and 10.94% of women had DSI. Eastern and southern countries had a higher prevalence of DSI. Multivariable analyses showed that social isolation and poor self-rated health status were associated with DSI with ORs of 2.01 (1.77-2.29) and 2.33 (2.15-2.52), while higher income was associated with lower risk of DSI (OR of 0.83 (0.78-0.89). Considering country-level socioeconomic factors, Human Development Index explained almost 38% of the variance of age-adjusted prevalence of DSI. CONCLUSION: There are important differences in terms of prevalence of DSI in Europe, depending on socioeconomic and medical factors. Prevention of DSI does represent an important challenge for maintaining quality of life in elderly population.

Retinal vascular structure independently predicts the initial treatment response in neovascular age-related macular degeneration.

PURPOSE: Prediction of the early treatment response is important in neovascular age-related macular degeneration (nAMD). Hence, we aimed to test if non-invasive measurements of the retinal vascular structure were able to predict a successful outcome of initial intravitreal treatment. METHODS: In 58 eyes of 58 patients with treatment-naïve nAMD, advanced markers of retinal vascular structure were measured by Singapore I Vessel Assessment prior to initial intravitreal treatment with three monthly injections of aflibercept with subsequently categorization of patients as full treatment responders (FTR) or non/partial treatment responders (N/PR), with the former defined as loosing fewer than five Early Treatment Diabetic Retinopathy Study letters and having no residual intra- or subretinal fluid or macular haemorrhage. RESULTS: Of 54 eyes attending follow-up, 44.4% were categorized as FTR. Patients with FTR were older (81.5 vs. 77 years, p = 0.04), and prior to treatment those eyes had a lower retinal arteriolar fractal dimension (Fd) (1.21 vs. 1.24 units, p = 0.02) and venular length-diameter ratio (LDR) (7.3 vs. 15.9 units, p = 0.006), but did not differ with respect to other retinal vascular parameters. In multiple logistic regression models, a lower chance of FTR was independently predicted by a higher retinal venular LDR (odds ratio [OR] 0.91, 95% CI 0.82-0.99, p = 0.03, for each 1 unit increment) and marginally by a higher retinal arteriolar Fd (OR 0.83, 95% CI 0.68-1.00, p = 0.05, for each 0.01 unit increment). CONCLUSION: Retinal venular LDR independently predicted the initial treatment response in nAMD. If confirmed by long-term, prospective studies, this might help to guide treatment.

Developing a Continuous Severity Scale for Macular Telangiectasia Type 2 Using Deep Learning and Implications for Disease Grading.

PURPOSE: Deep learning (DL) models have achieved state-of-the-art medical diagnosis classification accuracy. Current models are limited by discrete diagnosis labels, but could yield more information with diagnosis in a continuous scale. We developed a novel continuous severity scaling system for macular telangiectasia (MacTel) type 2 by combining a DL classification model with uniform manifold approximation and projection (UMAP). DESIGN: We used a DL network to learn a feature representation of MacTel severity from discrete severity labels and applied UMAP to embed this feature representation into 2 dimensions, thereby creating a continuous MacTel severity scale. PARTICIPANTS: A total of 2003 OCT volumes were analyzed from 1089 MacTel Project participants. METHODS: We trained a multiview DL classifier using multiple B-scans from OCT volumes to learn a previously published discrete 7-step MacTel severity scale. The classifiers' last feature layer was extracted as input for UMAP, which embedded these features into a continuous 2-dimensional manifold. The DL classifier was assessed in terms of test accuracy. Rank correlation for the continuous UMAP scale against the previously published scale was calculated. Additionally, the UMAP scale was assessed in the κ agreement against 5 clinical experts on 100 pairs of patient volumes. For each pair of patient volumes, clinical experts were asked to select the volume with more severe MacTel disease and to compare them against the UMAP scale. MAIN OUTCOME MEASURES: Classification accuracy for the DL classifier and κ agreement versus clinical experts for UMAP. RESULTS: The multiview DL classifier achieved top 1 accuracy of 63.3% (186/294) on held-out test OCT volumes. The UMAP metric showed a clear continuous gradation of MacTel severity with a Spearman rank correlation of 0.84 with the previously published scale. Furthermore, the continuous UMAP metric achieved κ agreements of 0.56 to 0.63 with 5 clinical experts, which was comparable with interobserver κ values. CONCLUSIONS: Our UMAP embedding generated a continuous MacTel severity scale, without requiring continuous training labels. This technique can be applied to other diseases and may lead to more accurate diagnosis, improved understanding of disease progression, and key imaging features for pathologic characteristics. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.