Test-Retest Variability and Discriminatory Power of Measurements From Microperimetry and Dark Adaptation Assessment in People With Intermediate Age-Related Macular Degeneration - A MACUSTAR Study Report.

Purpose: The purpose of this study was to assess test-retest variability and discriminatory power of measures from macular integrity assessment (S-MAIA) and AdaptDx. Methods: This is a cross-sectional study of 167 people with intermediate age-related macular degeneration (iAMD), no AMD (controls; n = 54), early AMD (n = 28), and late AMD (n = 41), recruited across 18 European ophthalmology centers. Repeat measures of mesopic and scotopic S-MAIA average (mean) threshold (MMAT decibels [dB] and SMAT [dB]) and rod intercept time (RIT [mins]) at 2 visits 14 (±7) days apart were recorded. Repeat measures were assessed by Bland-Altman analysis, intra-class correlation coefficients (ICCs) and variability ratios. Secondary analysis assessed the area under the receiver operating characteristic curves (AUC) to determine the ability to distinguish people as having no AMD, early AMD, or iAMD. Results: Data were available for 128, 131, and 103 iAMD participants for the mesopic and scotopic S-MAIA and AdaptDx, respectively. MMAT and SMAT demonstrate similar test-retest variability in iAMD (95% confidence interval [CI] ICC of 0.79-0.89 and 0.78-0.89, respectively). ICCs were worse in RIT (95% CI ICC = 0.55-0.77). All tests had equivalent AUCs (approximately 70%) distinguishing between subjects with iAMD and controls, whereas early AMD was indistinguishable from iAMD on all measures (AUC = <55%). A learning effect was not seen in these assessments under the operating procedures used. Conclusions: MMAT, SMAT, and RIT have adequate test-retest variability and are all moderately good at separating people with iAMD from controls. Translational Relevance: Expected levels of test-retest variability and discriminatory power of the AdaptDx and MAIA devices in a clinical study setting must be considered when designing future trials for people with AMD.

Assessment of the Classification of Age-Related Macular Degeneration Severity from the Northern Ireland Sensory Ageing Study Using a Measure of Dark Adaptation.

Purpose: To assess the differences in rod-mediated dark adaptation (RMDA) between different grades of age-related macular degeneration (AMD) severity using an OCT-based criterion compared with those of AMD severity using the Beckman color fundus photography (CFP)-based classification and to assess the association between the presence of subretinal drusenoid deposits (SDDs) and RMDA at different grades of AMD severity using an OCT-based classification. Design: Cross-sectional study. Participants: Participants from the Northern Ireland Sensory Ageing study (Queen's University Belfast). Methods: Complete RMDA (rod-intercept time [RIT]) data, CFP, and spectral-domain OCT images were extracted. Participants were stratified into 4 Beckman groups (omitting late-stage AMD) and 3 OCT-based groups. The presence and stage of SDDs were identified using OCT. Main Outcome Measures: Rod-intercept time data (age-corrected). Results: Data from 459 participants (median [interquartile range] age, 65 [59-71] years) were stratified by both the classifications. Subretinal drusenoid deposits were detected in 109 eyes. The median (interquartile range) RMDA for the Beckman classification (Beckman 0-3, with 3 being intermediate age-related macular degeneration [iAMD]) groups was 6.0 (4.5-8.7), 6.6 (4.7-10.5), 5.7 (4.4-7.4), and 13.2 (6-21.1) minutes, respectively. OCT classifications OCT0-OCT2 yielded different median (interquartile range) values: 5.8 (4.5-8.5), 8.4 (5.2-13.3), and 11.1 (5.3-20.1) minutes, respectively. After correcting for age, eyes in Beckman 3 (iAMD) had statistically significantly worse RMDA than eyes in the other Beckman groups (P ≤ 0.005 for all), with no statistically significant differences between the other Beckman groups. Similarly, after age correction, eyes in OCT2 had worse RMDA than eyes in OCT0 (P ≤ 0.001) and OCT1 (P < 0.01); however, there was no statistically significant difference between eyes in OCT0 and eyes in OCT1 (P = 0.195). The presence of SDDs was associated with worse RMDA in OCT2 (P < 0.01) but not in OCT1 (P = 0.285). Conclusions: Eyes with a structural definition of iAMD have delayed RMDA, regardless of whether a CFP- or OCT-based criterion is used. In this study, after correcting for age, the RMDA did not differ between groups of eyes defined to have early AMD or normal aging, regardless of the classification. The presence of SDDs has some effect on RMDA at different grades of AMD severity.

Optimising assessment of dark adaptation data using time to event analysis.

In age-related macular degeneration (AMD) research, dark adaptation has been found to be a promising functional measurement. In more severe cases of AMD, dark adaptation cannot always be recorded within a maximum allowed time for the test (~ 20-30 min). These data are recorded either as censored data-points (data capped at the maximum test time) or as an estimated recovery time based on the trend observed from the data recorded within the maximum recording time. Therefore, dark adaptation data can have unusual attributes that may not be handled by standard statistical techniques. Here we show time-to-event analysis is a more powerful method for analysis of rod-intercept time data in measuring dark adaptation. For example, at 80% power (at α = 0.05) sample sizes were estimated to be 20 and 61 with uncapped (uncensored) and capped (censored) data using a standard t-test; these values improved to 12 and 38 when using the proposed time-to-event analysis. Our method can accommodate both skewed data and censored data points and offers the advantage of significantly reducing sample sizes when planning studies where this functional test is an outcome measure. The latter is important because designing trials and studies more efficiently equates to newer treatments likely being examined more efficiently.

Factors associated with non-attendance in the Irish national diabetic retinopathy screening programme (INDEAR study report no. 2).

AIMS: We aimed to determine the patient and screening-level factors that are associated with non-attendance in the Irish National Diabetic Retinal screening programme (Diabetic RetinaScreen). To accomplish this, we modelled a selection of predictors derived from the historical screening records of patients with diabetes. METHODS: In this cohort study, appointment data from the national diabetic retinopathy screening programme (RetinaScreen) were extracted and augmented using publicly available meteorological and geospatial data. A total of 653,969 appointments from 158,655 patients were included for analysis. Mixed-effects models (univariable and multivariable) were used to estimate the influence of several variables on non-attendance to screening appointments. RESULTS: All variables considered for analysis were statistically significant. Variables of note, with meaningful effect, were age (OR: 1.23 per decade away from 70; 95% CI: [1.22-1.24]), type 2 diabetes (OR: 1.10; 95% CI: [1.06-1.14]) and socio-economic deprivation (OR: 1.12; 95% CI: [1.09-1.16]). A majority (52%) of missed appointments were from patients who had missed three or more appointments. CONCLUSIONS: This study is the first to outline factors that are associated with non-attendance within the Irish national diabetic retinopathy screening service. In particular, when corrected for age and other factors, patients with type 2 diabetes had higher rates of non-attendance. Additionally, this is the first study of any diabetic screening programme to demonstrate that weather may influence attendance. This research provides unique insight to guide the implementation of an optimal and cost-effective intervention strategy to improve attendance.

Glaucoma Home Monitoring Using a Tablet-Based Visual Field Test (Eyecatcher): An Assessment of Accuracy and Adherence Over 6 Months.

PURPOSE: To assess accuracy and adherence of visual field (VF) home monitoring in a pilot sample of patients with glaucoma. DESIGN: Prospective longitudinal feasibility and reliability study. METHODS: Twenty adults (median 71 years) with an established diagnosis of glaucoma were issued a tablet perimeter (Eyecatcher) and were asked to perform 1 VF home assessment per eye, per month, for 6 months (12 tests total). Before and after home monitoring, 2 VF assessments were performed in clinic using standard automated perimetry (4 tests total, per eye). RESULTS: All 20 participants could perform monthly home monitoring, though 1 participant stopped after 4 months (adherence: 98% of tests). There was good concordance between VFs measured at home and in the clinic (r = 0.94, P < .001). In 21 of 236 tests (9%), mean deviation deviated by more than ±3 dB from the median. Many of these anomalous tests could be identified by applying machine learning techniques to recordings from the tablets' front-facing camera (area under the receiver operating characteristic curve = 0.78). Adding home-monitoring data to 2 standard automated perimetry tests made 6 months apart reduced measurement error (between-test measurement variability) in 97% of eyes, with mean absolute error more than halving in 90% of eyes. Median test duration was 4.5 minutes (quartiles: 3.9-5.2 minutes). Substantial variations in ambient illumination had no observable effect on VF measurements (r = 0.07, P = .320). CONCLUSIONS: Home monitoring of VFs is viable for some patients and may provide clinically useful data.

Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma.

Glaucoma is a leading cause of irreversible sight-loss and has been shown to affect natural eye-movements. These changes may provide a cheap and easy-to-obtain biomarker for improving disease detection. Here, we investigated whether these changes are large enough to be clinically useful. We used a gaze-contingent simulated visual field (VF) loss paradigm, in which participants experienced a variable magnitude of simulated VF loss based on longitudinal data from a real glaucoma patient (thereby controlling for other variables, such as age and general health). Fifty-five young participants with healthy vision were asked to view two short videos and three pictures, either with: (1) no VF loss, (2) moderate VF loss, or (3) advanced VF loss. Eye-movements were recorded using a remote eye tracker. Key eye-movement parameters were computed, including saccade amplitude, the spread of saccade endpoints (bivariate contour ellipse area), location of saccade landing positions, and similarity of fixations locations among participants (quantified using kernel density estimation). The simulated VF loss caused some statistically significant effects in the eye movement parameters. Yet, these effects were not capable of consistently identifying simulated VF loss, despite it being of a magnitude likely easily detectable by standard automated perimetry.

Portable Perimetry Using Eye-Tracking on a Tablet Computer-A Feasibility Assessment.

PURPOSE: Visual field (VF) examination by standard automated perimetry (SAP) is an important method of clinical assessment. However, the complexity of the test, and its use of bulky, expensive equipment makes it impractical for case-finding. We propose and evaluate a new approach to paracentral VF assessment that combines an inexpensive eye-tracker with a portable tablet computer ("Eyecatcher"). METHODS: Twenty-four eyes from 12 glaucoma patients, and 12 eyes from six age-similar controls were examined. Participants were tested monocularly (once per eye), with both the novel Eyecatcher test and traditional SAP (HFA SITA standard 24-2). For Eyecatcher, the participant's task was to simply to look at a sequence of fixed-luminance dots, presented relative to the current point of fixation. Start and end fixations were used to determine locations where stimuli were seen/unseen, and to build a continuous map of sensitivity loss across a VF of approximately 20°. RESULTS: Eyecatcher was able to clearly separate patients from controls, and the results were consistent with those from traditional SAP. In particular, mean Eyecatcher scores were strongly correlated with mean deviation scores (r2 = 0.64, P < 0.001), and there was good concordance between corresponding VF locations (∼84%). Participants reported that Eyecatcher was more enjoyable, easier to perform, and less tiring than SAP (all P < 0.001). CONCLUSIONS: Portable perimetry using an inexpensive eye-tracker and a tablet computer is feasible, although possible means of improvement are suggested. TRANSLATIONAL RELEVANCE: Such a test could have significant utility as a case finding device.

Patient-reported Outcomes, Functional Assessment, and Utility Values in Glaucoma.

In clinical glaucoma research, the measurement of patient reported outcomes, functional assessment of disability, and health economic impact is critical. However, valid, time-efficient and comprehensive tools are not available and several current instruments lack in the appropriate precision for measuring the various dimensions of glaucoma-related quality of life (QoL), including functioning and mobility. Furthermore, statistical methods are inconsistently and sometimes incorrectly used in otherwise sound clinical studies. Standardizing and improving methods of patient-centered data collection and analysis in glaucoma studies are imperative. This paper outlines recommendations and provides a discussion of some of the pertinent issues relating to the optimization of patient-reported outcomes research in glaucoma.

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study.

BACKGROUND: Progressive optic nerve damage in glaucoma results in vision loss, quantifiable with visual field (VF) testing. VF measurements are, however, highly variable, making identification of worsening vision ('progression') challenging. Glaucomatous optic nerve damage can also be measured with imaging techniques such as optical coherence tomography (OCT). OBJECTIVE: To compare statistical methods that combine VF and OCT data with VF-only methods to establish whether or not these allow (1) more rapid identification of glaucoma progression and (2) shorter or smaller clinical trials. DESIGN: Method 'hit rate' (related to sensitivity) was evaluated in subsets of the United Kingdom Glaucoma Treatment Study (UKGTS) and specificity was evaluated in 72 stable glaucoma patients who had 11 VF and OCT tests within 3 months (the RAPID data set). The reference progression detection method was based on Guided Progression Analysis™ (GPA) Software (Carl Zeiss Meditec Inc., Dublin, CA, USA). Index methods were based on previously described approaches [Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS), Permutation analyses Of Pointwise Linear Regression (PoPLR) and structure-guided ANSWERS (sANSWERS)] or newly developed methods based on Permutation Test (PERM), multivariate hierarchical models with multiple imputation for censored values (MaHMIC) and multivariate generalised estimating equations with multiple imputation for censored values (MaGIC). SETTING: Ten university and general ophthalmology units (UKGTS) and a single university ophthalmology unit (RAPID). PARTICIPANTS: UKGTS participants were newly diagnosed glaucoma patients randomised to intraocular pressure-lowering drops or placebo. RAPID participants had glaucomatous VF loss, were on treatment and were clinically stable. INTERVENTIONS: 24-2 VF tests with the Humphrey Field Analyzer and optic nerve imaging with time-domain (TD) Stratus OCT™ (Carl Zeiss Meditec Inc., Dublin, CA, USA). MAIN OUTCOME MEASURES: Criterion hit rate and specificity, time to progression, future VF prediction error, proportion progressing in UKGTS treatment groups, hazard ratios (HRs) and study sample size. RESULTS: Criterion specificity was 95% for all tests; the hit rate was 22.2% for GPA, 41.6% for PoPLR, 53.8% for ANSWERS and 61.3% for sANSWERS (all comparisons p ≤ 0.042). Mean survival time (weeks) was 93.6 for GPA, 82.5 for PoPLR, 72.0 for ANSWERS and 69.1 for sANSWERS. The median prediction errors (decibels) when the initial trend was used to predict the final VF were 3.8 (5th to 95th percentile 1.7 to 7.6) for PoPLR, 3.0 (5th to 95th percentile 1.5 to 5.7) for ANSWERS and 2.3 (5th to 95th percentile 1.3 to 4.5) for sANSWERS. HRs were 0.57 [95% confidence interval (CI) 0.34 to 0.90; p = 0.016] for GPA, 0.59 (95% CI 0.42 to 0.83; p = 0.002) for PoPLR, 0.76 (95% CI 0.56 to 1.02; p = 0.065) for ANSWERS and 0.70 (95% CI 0.53 to 0.93; p = 0.012) for sANSWERS. Sample size estimates were not reduced using methods including OCT data. PERM hit rates were between 8.3% and 17.4%. Treatment effects were non-significant in MaHMIC and MaGIC analyses; statistical significance was altered little by incorporating imaging. LIMITATIONS: TD OCT is less precise than current imaging technology; current OCT technology would likely perform better. The size of the RAPID data set limited the precision of criterion specificity estimates. CONCLUSIONS: The sANSWERS method combining VF and OCT data had a higher hit rate and identified progression more quickly than the reference and other VF-only methods, and produced more accurate estimates of the progression rate, but did not increase treatment effect statistical significance. Similar studies with current OCT technology need to be undertaken and the statistical methods need refinement. TRIAL REGISTRATION: Current Controlled Trials ISRCTN96423140. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 4. See the NIHR Journals Library website for further project information. Data analysed in the study were from the UKGTS. Funding for the UKGTS was provided through an unrestricted investigator-initiated research grant from Pfizer Inc. (New York, NY, USA), with supplementary funding from the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Imaging equipment loans were made by Heidelberg Engineering, Carl Zeiss Meditec and Optovue (Fremont, CA, USA). Pfizer, Heidelberg Engineering, Carl Zeiss Meditec and Optovue had no input into the design, conduct, analysis or reporting of any of the UKGTS findings or this work. The sponsor for both the UKGTS and RAPID data collection was Moorfields Eye Hospital NHS Foundation Trust. David F Garway-Heath, Tuan-Anh Ho and Haogang Zhu are partly funded by the NIHR Biomedical Research Centre based at Moorfields Eye Hospital and UCL Institute of Ophthalmology. David F Garway-Heath's chair at University College London (UCL) is supported by funding from the International Glaucoma Association.

More frequent, more costly? Health economic modelling aspects of monitoring glaucoma patients in England.

BACKGROUND: Chronic open angle glaucoma (COAG) is an age-related eye disease causing irreversible loss of visual field (VF). Health service delivery for COAG is challenging given the large number of diagnosed patients requiring lifelong periodic monitoring by hospital eye services. Yet frequent examination better determines disease worsening and speed of VF loss under treatment. We examine the cost-effectiveness of increasing frequency of VF examinations during follow-up using a health economic model. METHODS: Two different VF monitoring schemes defined as current practice (annual VF testing) and proposed practice (three VF tests per year in the first 2 years after diagnosis) were examined. A purpose written health economic Markov model is used to test the hypothesis that cost effectiveness improves by implementing proposed practice on groups of patients stratified by age and severity of COAG. Further, a new component of the model, estimating costs of visual impairment, was added. Results were derived from a simulated cohort of 10000 patients with quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs) used as main outcome measures. RESULTS: An ICER of £21,392 per QALY was derived for proposed practice improving to a value of £11,382 once savings for prevented visual impairment was added to the model. Proposed practice was more cost-effective in younger patients. Proposed practice for patients with advanced disease at diagnosis generated ICERs > £60,000 per QALY; these cases would likely be on the most intensive treatment pathway making clinical information on speed of VF loss redundant. Sensitivity analysis indicated results to be robust in relation to hypothetical willingness to pay threshold identified by national guidelines, although greatest uncertainty was allied to estimates of implementation and visual impairment costs. CONCLUSION: Increasing VF monitoring at the earliest stages of follow-up for COAG appears to be cost-effective depending on reasonable assumptions about implementation costs. Our health economic model highlights benefits of stratifying patients to more or less monitoring based on age and stage of disease at diagnosis; a prospective study is needed to prove these findings. Further, this works highlights gaps in knowledge about long term costs of visual impairment.

Quantifying discordance between structure and function measurements in the clinical assessment of glaucoma.

OBJECTIVE: To evaluate a new method of quantifying and visualizing discordance between structural and functional measurements in glaucomatous eyes by predicting the visual field (VF) from retinal nerve fiber layer thickness (RNFLT) using a bayesian radial basis function. METHODS: Five GDx VCC RNFLT scans and 5 Humphrey 24-2 Swedish Interactive Thresholding Algorithm VF tests were performed for 50 glaucomatous eyes from 50 patients. A best-available estimate (BAE) of the true VF was calculated as the pointwise median of these 5 replications. This BAE VF was compared with every RNFLT-predicted VF from the bayesian radial basis function and every measured VF. Predictability of VFs from RNFLT was established from previous data. A structure-function pattern discordance map and a structure-function discordance index (scores of 0-1) were established from the predictability limits for each structure-function measurement pair to quantify and visualize the discordance between the structure-predicted and measured VFs. RESULTS: The mean absolute difference between the structure-predicted and BAE VFs was 3.9 dB. The mean absolute difference between measured and BAE VFs was 2.6 dB. The mean (SD) structure-function discordance index score was 0.34 (0.11). Ninety-seven (39%) of the structure-predicted VFs showed significant discordance (structure-function discordance index score >0.3) from measured VFs. CONCLUSIONS: On average, the bayesian radial basis function predicts the BAE VF from RNFLT slightly less well than a measured VF from the 5 VFs composing the BAE VF. The pattern discordance map highlights locations with structure-function discordance, with the structure-function discordance index providing a summary index. These tools may help clinicians trust the mutually confirmatory structure-function measurements with good concordance or identify unreliable ones with poor concordance.