New insights into measurement variability in glaucomatous visual fields from computer modelling

Multiple (frontloaded) visual field tests increase identification of very slow mean deviation progression in glaucoma

OBJECTIVE

To determine the effect of frontloading (multiple) visual field (VF) tests at the same visit for detecting mean deviation (MD) change in slowly progressive glaucoma.

METHODS

This was a computer simulation study. Baseline MD (range, 0 to -12 dB) and progression rate (range, 0 to -0.4 dB/year, non-inclusive) were generated for 10,000 patients. Each patient had 6 simulated "stable" baseline VF tests. Then follow-up VFs (up to 10 years) were generated by incorporating progression rate and within-visit and between-visit variability. The independent variables were number of VF tests per visit (one non-frontloaded or two frontloaded), VF reliability (100%, 85%, or 70%), repeat testing because of unreliable results (yes or no), and follow-up interval (6-monthly or yearly). The outcomes were detection of progression (MD slope that was negative and significant at p < 0.05), MD at detection, and number of years to detection.

RESULTS

Frontloading identified more progressors (62.7%-79.2%) compared with non-frontloading (31.0%-36.7%) at 10 years (p < 0.0001). Six-monthly follow-ups led to greater detection than yearly intervals. Progressors detected by both methods were detected by the non-frontloaded method sooner (up to 0.26 years), but this was small and not clinically significant (MD difference, 0.06 dB). An increase (less severe) in MD, an increase (slower) in progression rate, and an increase in SD of baseline VFs decreased the likelihood of detecting progression.

CONCLUSIONS

Frontloading VF tests at 6-monthly intervals improve detection rates of MD progression in slowly progressive glaucoma patients compared with performing 1 test per visit at yearly intervals.

Mapping vision loss of patients in a glaucoma backlog following the COVID-19 pandemic: a real-world analysis using the Glauc-Strat-Fast risk stratification tool

INTRODUCTION

Glauc-Strat-Fast is a clinical tool recommended by The Royal College of Ophthalmologists to classify glaucoma patients into strata of risk for significant future sight loss and an estimate of resource requirement. The aim of this study was to map the movement of glaucoma patients across stratification boundaries on Glauc-Strat-Fast during the COVID-19 pandemic.

SUBJECTS AND METHODS

Glauc-Strat-Fast was applied to a consecutive sample of 100 primary open angle glaucoma patients in a backlog at Worcestershire Acute Hospitals NHS Trust. Stratification outcomes were compared between clinic visits prior to the COVID-19 pandemic versus the follow-up visit. Patients were stratified twice separately based on their worse eye (i.e., most affected) and better eye (i.e., least affected) according to Glauc-Strat-Fast.

RESULTS

Amount of slippage (difference between target follow-up and actual follow-up) ranged from 2 to 32 months. There was a statistically significant average reduction in visual field mean deviation for better and worse eyes between visits (p = <0.001). At follow-up, no worse eyes were classified as being low risk (green), while 96 were classified as high risk (red). For better eyes, elevation of risk into the highest strata of Glauc-Strat-Fast observed a three-fold increase in patients (19 versus 56) between visits.

DISCUSSION

This retrospective real-world analysis highlights patients' movement into the highest strata on the Glauc-Strat-Fast tool and demonstrates a significant deterioration in visual outcomes during a period of extensive appointment slippage. The findings demonstrate the utility of Glauc-Strat-Fast as a tool for improved patient management.

Understanding and identifying visual field progression

Detecting deterioration of visual field sensitivity measurements is important for the diagnosis and management of glaucoma. This review surveys the current methods for assessing progression that are implemented in clinical devices, which have been used in clinical trials, alongside more recent advances proposed in the literature. Advice is also offered to clinicians on what they can do to improve the collection of perimetric data to help analytical progression methods more accurately predict change. This advice includes a discussion of how frequently visual field testing should be undertaken, with a view towards future developments, such as digital healthcare outside the standard clinical setting and more personalised approaches to perimetry.

A Data-Driven Model for Simulating Longitudinal Visual Field Tests in Glaucoma

Purpose

To develop a simulation model for glaucomatous longitudinal visual field (VF) tests with controlled progression rates.

Methods

Longitudinal VF tests of 1008 eyes from 755 patients with glaucoma were used to learn the statistical characteristics of VF progression. The learned statistics and known anatomic correlations between VF test points were used to automatically generate progression patterns for baseline fields of patients with glaucoma. VF sequences were constructed by adding spatially correlated noise templates to the generated progression patterns. The two one-sided test (TOST) procedure was used to analyze the equivalence between simulated data and data from patients with glaucoma. VF progression detection rates in the simulated VF data were compared to those in patients with glaucoma using mean deviation (MD), cluster, and pointwise trend analysis.

Results

VF indices (MD, pattern standard deviation), MD linear regression slopes, and progression detection rates for the simulated and patients' data were practically equivalent (TOST P < 0.01). In patients with glaucoma, the detection rates in 7 years using MD, cluster, and pointwise trend analysis were 24.4%, 26.2%, and 38.4%, respectively. In the simulated data, the mean detection rates (95% confidence interval) for MD, cluster, and pointwise trend analysis were 24.7% (24.1%-25.2%), 24.9% (24.2%-25.5%), and 35.7% (34.9%-36.5%), respectively.

Conclusions

A novel simulation model generates glaucomatous VF sequences that are practically equivalent to longitudinal VFs from patients with glaucoma.

Translational Relevance

Simulated VF sequences with controlled progression rates can support the evaluation and optimization of methods to detect VF progression and can provide guidance for the interpretation of longitudinal VFs.

Longitudinal visual field variability and the ability to detect glaucoma progression in black and white individuals

BACKGROUND/AIMS

To investigate racial differences in the variability of longitudinal visual field testing in a 'real-world' clinical population, evaluate how these differences are influenced by socioeconomic status, and estimate the impact of differences in variability on the time to detect visual field progression.

METHODS

This retrospective observational cohort study used data from 1103 eyes from 751 White individuals and 428 eyes from 317 black individuals. Linear regression was performed on the standard automated perimetry mean deviation values for each eye over time. The SD of the residuals from the trend lines was calculated and used as a measure of variability for each eye. The association of race with the SD of the residuals was evaluated using a multivariable generalised estimating equation model with an interaction between race and zip code income. Computer simulations were used to estimate the time to detect visual field progression in the two racial groups.

RESULTS

Black patients had larger visual field variability over time compared with white patients, even when adjusting for zip code level socioeconomic variables (SD of residuals for Black patients=1.53 dB (95% CI 1.43 to 1.64); for white patients=1.26 dB (95% CI 1.14 to 1.22); mean difference: 0.28 (95% CI 0.15 to 0.41); p<0.001). The difference in visual field variability between black and white patients was greater at lower levels of income and led to a delay in detection of glaucoma progression.

CONCLUSION

Black patients had larger visual field variability compared with white patients. This relationship was strongly influenced by socioeconomic status and may partially explain racial disparities in glaucoma outcomes.

Glaucomatous Visual Field Progression in the African Descent and Glaucoma Evaluation Study (ADAGES): Eleven Years of Follow-up

PURPOSE

To compare the rates of visual field (VF) progression between individuals of Black and White race and to investigate whether treatment effects may help explain differences previously reported between racial groups.

DESIGN

Multicenter prospective observational cohort study.

METHODS

Participants were patients in referral tertiary care glaucoma clinics with open angle glaucoma. Eyes were excluded who had <5 VF tests and <2 years of follow-up or any disease that could affect the optic nerve or the VF. The VF mean deviation (MD) slopes over time (dB/y) were calculated with linear regression models. Socioeconomic variables, rates of glaucoma surgery, medications, treated intraocular pressure (IOP), and central corneal thickness (CCT) were investigated.

RESULTS

A total of 516 eyes were included with a mean (95% CI) follow-up time of 11.0 (range, 10.5-11.5) years and 15.0 (range, 14.1-15.8) visits. Participants of Black race were significantly younger (59.7 vs 66.9 years, P < .01) than those of White race. The mean CCT and socioeconomic variables were similar between Black and White groups (P = 0.20 and P = .56, respectively), as were treatment with topical medications (P = .90) and the rate of VF MD change (-0.24 [-0.31 to -0.17] dB/year vs -0.32 [-0.36 to -0.27], P = .11), despite higher treated mean IOP (14.9 [14.5 to 15.4] vs 14.0 [13.6 to 14.4] mm Hg, P = .03) and fewer trabeculectomies (29.5% vs 50.0%, P < .01) in the Black race group.

CONCLUSIONS

Rates of VF progression were similar despite higher treated IOP in the Black race group. Mitigation of health access disparities in this study may have equalized previously reported different rates of VF progression between racial groups.

Rates of Glaucoma Progression Derived from Linear Mixed Models Using Varied Random Effect Distributions

Purpose

To compare the ability of linear mixed models with different random effect distributions to estimate rates of visual field loss in glaucoma patients.

Methods

Eyes with five or more reliable standard automated perimetry (SAP) tests were identified from the Duke Glaucoma Registry. Mean deviation (MD) values from each visual field and associated timepoints were collected. These data were modeled using ordinary least square (OLS) regression and linear mixed models using the Gaussian, Student's t, or log-gamma (LG) distributions as the prior distribution for random effects. Model fit was compared using the Watanabe–Akaike information criterion (WAIC). Simulated eyes of varying initial disease severity and rates of progression were created to assess the accuracy of each model in predicting the rate of change and likelihood of declaring progression.

Results

A total of 52,900 visual fields from 6558 eyes of 3981 subjects were included. Mean follow-up period was 8.7 ± 4.0 years, with an average of 8.1 ± 3.7 visual fields per eye. The LG model produced the lowest WAIC, demonstrating optimal model fit. In simulations, the LG model declared progression earlier than OLS (P < 0.001) and had the greatest accuracy in predicted slopes (P < 0.001). The Gaussian model significantly underestimated rates of progression among fast and catastrophic progressors.

Conclusions

Linear mixed models using the LG distribution outperformed conventional approaches for estimating rates of SAP MD loss in a population with glaucoma.

Translational Relevance

Use of the LG distribution in models estimating rates of change among glaucoma patients may improve their accuracy in rapidly identifying progressors at high risk for vision loss.

Predicting rapid progression phases in glaucoma using a soft voting ensemble classifier exploiting Kalman filtering

In managing patients with chronic diseases, such as open angle glaucoma (OAG), the case treated in this paper, medical tests capture the disease phase (e.g. regression, stability, progression, etc.) the patient is currently in. When medical tests have low residual variability (e.g. empirical difference between the patient's true and recorded value is small) they can effectively, without the use of sophisticated methods, identify the patient's current disease phase; however, when medical tests have moderate to high residual variability this may not be the case. This paper presents a framework for handling the latter case. The framework presented integrates the outputs of interacting multiple model Kalman filtering with supervised learning classification. The purpose of this integration is to estimate the true values of patients' disease metrics by allowing for rapid and non-rapid phases; and dynamically adapting to changes in these values over time. We apply our framework to classifying whether a patient with OAG will experience rapid progression over the next two or three years from the time of classification. The performance (AUC) of our model increased by approximately 7% (increased from 0.752 to 0.819) when the Kalman filtering results were incorporated as additional features in the supervised learning model. These results suggest the combination of filters and statistical learning methods in clinical health has significant benefits. Although this paper applies our methodology to OAG, the methodology developed is applicable to other chronic conditions.

Improving the Power of Glaucoma Neuroprotection Trials Using Existing Visual Field Data

PURPOSE

Selecting reliable visual field (VF) test takers could improve the power of randomized clinical trials in glaucoma. We test this hypothesis via simulations using a large real world data set.

DESIGN

Methodology analysis: assessment of how improving reliability affects sample size estimates.

METHODS

A variability index (VI) estimating intertest variability was calculated for each subject using the residuals of the regression of the mean deviation over time for the first 6 tests in a series of at least 10 examinations for 2,804 patients. Using data from the rest of the series, we simulate VFs at regular intervals for 2 years. To simulate the neuroprotective effect (NE), we reduced the observed progression rate by 20%, 30%, or 50%. The main outcome measure was the sample size to detect a significant difference (P < .05) at 80% power.

RESULTS

In the first experiment, we simulated a trial including one eye per subject, either selecting randomly from the database or prioritizing patients with low VI. We could not reach 80% power for the low NE with the available patients, but the sample size was reduced by 38% and 49% for the 30% and 50% NE, respectively. In the second experiment, we simulated 2 eyes per subject, one of which was the control eye. The sample size (smaller overall) was reduced by 26% and 38% for the 30% and 50% NE by prioritizing patients with low VI.

CONCLUSIONS

Selecting patients with low intertest variability can significantly improve the power and reduce the sample size needed in a trial.

Progression to blindness in 20 years among patients with glaucomatous visual field loss in a tertiary hospital in the Philippines

Objective

To determine visual field (VF) rates of change among patients with glaucomatous VF loss and proportion of those becoming blind based on residual life expectancy and factors associated with fast progression.

Methods and analysis

This was a retrospective study of the VFs of patients with glaucomatous VF defects in at least one eye. Baseline and final VFs were reviewed. Rates of VF change (decibels (dB)/year) for each eye, together with the residual life expectancy based on age and sex, were used to predict mean deviation/defect (MD) at the end of expected lifetime. Blindness was defined if computed MD was 22 dB (Octopus) or −22 dB (Humphrey) or worse in the better eye. Factors associated with fast progression (>1 dB/year for Octopus or <−1 dB/year for Humphrey) and blindness were determined.

Results

There were 1016 eyes of 583 patients eligible. There was decline in VF MD/year in 613/1016 (60.3%), 95% CI (57.3% to 63.3%) of eyes; however, only 98/1016 (9.7%), 95% CI (7.9% to 11.5%) of eyes showed fast progression. Among patients with bilateral VFs, 43/433 (9.9%), 95% CI (7.1 to 12.8) of eyes were predicted to progress to blindness. In multivariate analysis, factors associated with fast progression were baseline MD (p<0.001) and male sex (p=0.041). Factors associated with blindness were age <60 years (p=0.003), baseline MD (p=0.022), bilateral glaucomatous VF defects (p=<0.001) and fast progression (p<0.001).

Conclusion

Patients reaching blindness in a routine clinical setting was 10%. Because of association of age and baseline MD on blindness, early disease detection is important. VF progression rates and residual life expectancy must be incorporated in glaucoma care.

Comparison of Short- And Long-Term Variability in Standard Perimetry and Spectral Domain Optical Coherence Tomography in Glaucoma

PURPOSE

To assess short- and long-term variability on standard automated perimetry (SAP) and spectral domain optical coherence tomography (SD-OCT) in glaucoma.

DESIGN

Prospective cohort.

METHODS

Ordinary least squares linear regression of SAP mean deviation (MD) and SD-OCT global retinal nerve fiber layer (RNFL) thickness were fitted over time for sequential tests conducted within 5 weeks (short-term testing) and annually (long-term testing). Residuals were obtained by subtracting the predicted and observed values, and each patient's standard deviation (SD) of the residuals was used as a measure of variability. Wilcoxon signed-rank test was performed to test the hypothesis of equality between short- and long-term variability.

RESULTS

A total of 43 eyes of 43 glaucoma subjects were included. Subjects had a mean 4.5 ± 0.8 SAP and OCT tests for short-term variability assessment. For long-term variability, the same number of tests were performed and results annually collected over an average of 4.0 ± 0.8 years. The average SD of the residuals was significantly higher in the long-term than in the short-term period for both tests: 1.05 ± 0.70 dB vs. 0.61 ± 0.34 dB, respectively (P < 0.001) for SAP MD and 1.95 ± 1.86 μm vs. 0.81 ± 0.56 μm, respectively (P < 0.001) for SD-OCT RNFL thickness.

CONCLUSIONS

Long-term variability was higher than short-term variability on SD-OCT and SAP. Because current event-based algorithms for detection of glaucoma progression on SAP and SD-OCT have relied on short-term variability data to establish their normative databases, these algorithms may be underestimating the variability in the long-term and thus may overestimate progression over time.

Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder

In this manuscript we develop a deep learning algorithm to improve estimation of rates of progression and prediction of future patterns of visual field loss in glaucoma. A generalized variational auto-encoder (VAE) was trained to learn a low-dimensional representation of standard automated perimetry (SAP) visual fields using 29,161 fields from 3,832 patients. The VAE was trained on a 90% sample of the data, with randomization at the patient level. Using the remaining 10%, rates of progression and predictions were generated, with comparisons to SAP mean deviation (MD) rates and point-wise (PW) regression predictions, respectively. The longitudinal rate of change through the VAE latent space (e.g., with eight dimensions) detected a significantly higher proportion of progression than MD at two (25% vs. 9%) and four (35% vs 15%) years from baseline. Early on, VAE improved prediction over PW, with significantly smaller mean absolute error in predicting the 4th, 6th and 8th visits from the first three (e.g., visit eight: VAE8: 5.14 dB vs. PW: 8.07 dB; P < 0.001). A deep VAE can be used for assessing both rates and trajectories of progression in glaucoma, with the additional benefit of being a generative technique capable of predicting future patterns of visual field damage.

Quantification of Visual Field Variability in Glaucoma: Implications for Visual Field Prediction and Modeling

Purpose

To quantify visual field (VF) variability as a function of threshold sensitivity and location, and to compare weighted pointwise linear regression (PLR) with unweighted PLR and pointwise exponential regression (PER) for data fit and prediction ability.

Methods

Two datasets were used for this retrospective study. The first was used to characterize and estimate VF variability, and included a total of 4,747 eyes of 3,095 glaucoma patients with six or more VFs and 3 years or more of follow-up. After performing PER for each series, standard deviation of residuals was quantified for each decibel of sensitivity as a measure of variability. A separate dataset was used to test and compare unweighted PLR, weighted PLR, and PER for data fit and prediction, and included 261 eyes of 176 primary open-angle glaucoma patients with 10 or more VFs and 6 years or more of follow-up.

Results

The degree of variability changed as a function of threshold sensitivity with a zenith and a nadir at 33 and 11 dB, respectively. Variability decreased with eccentricity and was higher in the central 10° (P < 0.001). Differences among the methods for data fit were negligible. PER was the best model to predict future sensitivity values in the mid term and long term.

Conclusions

VF variability increases with the severity of glaucoma damage and decreases with eccentricity. Weighted linear regression neither improves model fit nor prediction. PER exhibited the best prediction ability, which is likely related to the nonlinear nature of long-term glaucomatous perimetric decay.

Translational Relevance

This study suggests that taking into account heteroscedasticity has no advantage in VF modeling.

Detection of Glaucoma Progression in Individuals of African Descent Compared With Those of European Descent

Importance

Individuals of African descent have been reported to be at higher risk for becoming visually impaired from glaucoma compared with individuals of European descent.

Objective

To investigate racial differences in longitudinal visual field variability and their impact on time to detect visual field progression.

Design, Setting, and Participants

This multicenter prospective observational cohort study included 236 eyes of 173 individuals of European descent and 235 eyes of 171 individuals of African descent followed up for a mean (SD) time of 7.5 (3.4) years.

Main Outcomes and Measures

Differences in test-retest variability and simulated time to detect progression in individuals of African descent and of European descent with glaucoma. Standard automated perimetry mean deviation values were regressed over time for each eye, and SD of the residuals was used as a measure of variability. Distributions of residuals were used in computer simulations to reconstruct "real-world" standard automated perimetry mean deviation trajectories under different assumptions about rate of change and frequency of testing. Times to detect progression were obtained for the simulated visual fields.

Results

Among the 344 patients, the mean (SD) age at baseline was 60.2 (10.0) and 60.6 (9.0) years for individuals of African descent and of European descent, respectively; 94 (52%) and 86 (48%) of individuals of African descent and of European descent were women, respectively. The mean SD of the residuals was larger in eyes of individuals of African descent vs those of European descent (1.45 [0.83] dB vs 1.12 [0.48] dB; mean difference: 0.33 dB; 95% CI of the difference, 0.21-0.46; P < .001). The eyes in individuals of African descent had a larger increase in variability with worsening disease (P < .001). When simulations were performed assuming common progression scenarios, there was a delay to detect progression in eyes of individuals of African descent compared with those of European descent. For a scenario with baseline mean deviation of -10 dB and rate of change of -0.5 dB/y, detection of progression in individuals of African descent was delayed by 3.1 (95% CI, 2.9-3.2) years, when considered 80% power and annual tests.

Conclusions and Relevance

Patients of African descent with glaucoma showed increased visual field variability compared with those of European descent, resulting in delayed detection of progression that may contribute to explain higher rates of glaucoma-related visual impairment in individuals of African descent compared with those of European descent with glaucoma.

Does eye examination order for standard automated perimetry matter?

Purpose

In spite of faster examination procedures, visual field (VF) results are potentially influenced by fatigue. We use large‐scale VF data collected from clinics to test the hypothesis that perimetric fatigue effects are greater in the eye examined second.

Methods

Series of six Humphrey Swedish Interactive Testing Algorithm (SITA) VFs from 6901 patients were retrospectively extracted from a VF database from four different glaucoma clinics. Mean deviation (MD) was compared between first and second tested eyes. A surrogate measure of longitudinal MD variability over time was estimated from errors using linear regression of MD against time then compared between first and second tested eye.

Results

Right eye VF was tested consistently first throughout in 6320 (91.6%) patients. Median (interquartile range; IQR) MD in the first tested (right) eye and second tested (left) eye was −2.57 (−6.15, −0.58) dB and −2.70 (−6.34, −0.80) dB respectively (median reduction VF sensitivity of 0.13 dB; p < 0.001). Median (IQR) increase in our surrogate measure of longitudinal MD variability in the second eye tested was 3% (−43%, 50%); this effect was not associated with patient age or rest time between examinations.

Conclusion

Statistically significant perimetric fatigue effects manifest on average in the second eye tested in routine clinics using Humphrey Field Analyzer SITA examinations. However, the average effects were very small and there was enormous variation among patients. We recommend starting with a right eye examination so that any perimetric fatigue effects, if they exist in an individual, will be as constant as possible from visit to visit.

Development of a Visual Field Simulation Model of Longitudinal Point-Wise Sensitivity Changes From a Clinical Glaucoma Cohort

Purpose

To develop a new visual field simulation model that can recreate real-world longitudinal results at a point-wise level from a clinical glaucoma cohort.

Methods

A cohort of 367 glaucoma eyes from 265 participants seen over 10.1 ± 2.5 years were included to obtain estimates of “true” longitudinal visual field point-wise sensitivity and estimates of measurement variability. These two components were then combined to reconstruct visual field results in a manner that accounted for correlated measurement error. To determine how accurately the simulated results reflected the clinical cohort, longitudinal variability estimates of mean deviation (MD) were determined by calculating the SD of the residuals from linear regression models fitted to the MD values over time for each eye in the simulated and clinical cohorts. The new model was compared to a previous model that does not account for spatially correlated errors.

Results

The SD of all the residuals for the clinical and simulated cohorts was 1.1 dB (95% confidence interval [CI]: 1.1–1.2 dB) and 1.1 dB (95% CI: 1.1–1.1 dB), respectively, whereas it was 0.4 dB (95% CI: 0.4–0.4 dB) using the previous simulation model that did not account for correlated errors.

Conclusions

A new simulation model accounting for correlated measurement errors between visual field locations performed better than a previous model in estimating visual field variability in glaucoma.

Translational Relevance

This model can provide a powerful framework to better understand use of visual field testing in clinical practice and trials and to evaluate new methods for detecting progression.

Example of monitoring measurements in a virtual eye clinic using ‘big data’

Aim

To assess the equivalence of measurement outcomes between patients attending a standard glaucoma care service, where patients see an ophthalmologist in a face-to-face setting, and a glaucoma monitoring service (GMS).

Methods

The average mean deviation (MD) measurement on the visual field (VF) test for 250 patients attending a GMS were compared with a ‘big data’ repository of patients attending a standard glaucoma care service (reference database). In addition, the speed of VF progression between GMS patients and reference database patients was compared. Reference database patients were used to create expected outcomes that GMS patients could be compared with. For GMS patients falling outside of the expected limits, further analysis was carried out on the clinical management decisions for these patients.

Results

The average MD of patients in the GMS ranged from +1.6dB to −18.9dB between two consecutive appointments at the clinic. In the first analysis, 12 (4.8%; 95% CI 2.5% to 8.2%) GMS patients scored outside the 90% expected values based on the reference database. In the second analysis, 1.9% (95% CI 0.4% to 5.4%) GMS patients had VF changes outside of the expected 90% limits.

Conclusions

Using ‘big data’ collected in the standard glaucoma care service, we found that patients attending a GMS have equivalent outcomes on the VF test. Our findings provide support for the implementation of virtual healthcare delivery in the hospital eye service.

The value of visual field testing in the era of advanced imaging: clinical and psychophysical perspectives

White‐on‐white standard automated perimetry (SAP) is widely used in clinical and research settings for assessment of contrast sensitivity using incremental light stimuli across the visual field. It is one of the main functional measures of the effect of disease upon the visual system. SAP has evolved over the last 40 years to become an indispensable tool for comprehensive assessment of visual function. In modern clinical practice, a range of objective measurements of ocular structure, such as optical coherence tomography, have also become invaluable additions to the arsenal of the ophthalmic examination. Although structure‐function correlation is a highly desirable determinant of an unambiguous clinical picture for a patient, in practice, clinicians are often faced with discordance of structural and functional results, which presents them with a challenge. The construction principles behind the development of SAP are used to discuss the interpretation of visual fields, as well as the problem of structure‐function discordance. Through illustrative clinical examples, we provide useful insights to assist clinicians in combining a range of clinical results obtained from SAP and from advanced imaging techniques into a coherent picture that can help direct clinical management.

Frequency of Testing to Detect Visual Field Progression Derived Using a Longitudinal Cohort of Glaucoma Patients

PURPOSE

To determine the time required to detect statistically significant progression for different rates of visual field loss using standard automated perimetry (SAP) when considering different frequencies of testing using a follow-up scheme that resembles clinical practice.

DESIGN

Observational cohort study.

PARTICIPANTS

One thousand seventy-two eyes of 665 patients with glaucoma followed up over an average of 4.3±0.9 years.

METHODS

Participants with 5 or more visual field tests over a 2- to 5-year period were included to derive the longitudinal measurement variability of SAP mean deviation (MD) using linear regressions. Estimates of variability then were used to reconstruct real-world visual field data by computer simulation to evaluate the time required to detect progression for various rates of visual field loss and different frequencies of testing. The evaluation was performed using a follow-up scheme that resembled clinical practice by requiring a set of 2 baseline tests and a confirmatory test to identify progression.

MAIN OUTCOME MEASURES

Time (in years) required to detect progression.

RESULTS

The time required to detect a statistically significant negative MD slope decreased as the frequency of testing increased, albeit not proportionally. For example, 80% of eyes with an MD loss of -2 dB/year would be detected after 3.3, 2.4, and 2.1 years when testing is performed once, twice, and thrice per year, respectively. For eyes with an MD loss of -0.5 dB/year, progression can be detected with 80% power after 7.3, 5.7, and 5.0 years, respectively.

CONCLUSIONS

This study provides information on the time required to detect progression using MD trend analysis in glaucoma eyes when different testing frequencies are used. The smaller gains in the time to detect progression when testing is increased from twice to thrice per year suggests that obtaining 2 reliable tests at baseline followed by semiannual testing and confirmation of progression through repeat testing in the initial years of follow-up may provide a good compromise for detecting progression, while minimizing the burden on health care resources in clinical practice.

A comparison of Goldmann III, V and spatially equated test stimuli in visual field testing: the importance of complete and partial spatial summation

PURPOSE

Goldmann size V (GV) test stimuli are less variable with a greater dynamic range and have been proposed for measuring contrast sensitivity instead of size III (GIII). Since GIII and GV operate within partial summation, we hypothesise that actual GV (aGV) thresholds could predict GIII (pGIII) thresholds, facilitating comparisons between actual GIII (aGIII) thresholds with pGIII thresholds derived from smaller GV variances. We test the suitability of GV for detecting visual field (VF) loss in patients with early glaucoma, and examine eccentricity-dependent effects of number and depth of defects. We also hypothesise that stimuli operating within complete spatial summation ('spatially equated stimuli') would detect more and deeper defects.

METHODS

Sixty normal subjects and 20 glaucoma patients underwent VF testing on the Humphrey Field Analyzer using GI-V sized stimuli on the 30-2 test grid in full threshold mode. Point-wise partial summation slope values were generated from GI-V thresholds, and we subsequently derived pGIII thresholds using aGV. Difference plots between actual GIII (aGIII) and pGIII thresholds were used to compare the amount of discordance. In glaucoma patients, the number of 'events' (points below the 95% lower limit of normal), defect depth and global indices were compared between stimuli.

RESULTS

90.5% of pGIII and aGIII points were within ±3 dB of each other in normal subjects. In the glaucoma cohort, there was less concordance (63.2% within ±3 dB), decreasing with increasing eccentricity. GIII found more defects compared to GV-derived thresholds, but only at outermost test locations. Greater defect depth was found using aGIII compared to aGV and pGIII, which increased with eccentricity. Global indices revealed more severe loss when using GIII compared to GV. Spatially equated stimuli detected the greatest number of 'events' and largest defect depth.

CONCLUSIONS

Whilst GV may be used to reliably predict GIII values in normal subjects, there was less concordance in glaucoma patients. Similarities in 'event' detection and defect depth in the central VF were consistent with the fact that GIII and GV operate within partial summation in this region. Eccentricity-dependent effects in 'events' and defect depth were congruent with changes in spatial summation across the VF and the increase in critical area with disease. The spatially equated test stimuli showed the greatest number of defective locations and larger sensitivity loss.

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.

Detection and measurement of clinically meaningful visual field progression in clinical trials for glaucoma

Glaucomatous visual field progression has both personal and societal costs and therefore has a serious impact on quality of life. At the present time, intraocular pressure (IOP) is considered to be the most important modifiable risk factor for glaucoma onset and progression. Reduction of IOP has been repeatedly demonstrated to be an effective intervention across the spectrum of glaucoma, regardless of subtype or disease stage. In the setting of approval of IOP-lowering therapies, it is expected that effects on IOP will translate into benefits in long-term patient-reported outcomes. Nonetheless, the effect of these medications on IOP and their associated risks can be consistently and objectively measured. This helps to explain why regulatory approval of new therapies in glaucoma has historically used IOP as the outcome variable. Although all approved treatments for glaucoma involve IOP reduction, patients frequently continue to progress despite treatment. It would therefore be beneficial to develop treatments that preserve visual function through mechanisms other than lowering IOP. The United States Food and Drug Administration (FDA) has stated that they will accept a clinically meaningful definition of visual field progression using Glaucoma Change Probability criteria. Nonetheless, these criteria do not take into account the time (and hence, the speed) needed to reach significant change. In this paper we provide an analysis based on the existing literature to support the hypothesis that decreasing the rate of visual field progression by 30% in a trial lasting 12-18 months is clinically meaningful. We demonstrate that a 30% decrease in rate of visual field progression can be reliably projected to have a significant effect on health-related quality of life, as defined by validated instruments designed to measure that endpoint.

Equating spatial summation in visual field testing reveals greater loss in optic nerve disease

PURPOSE

To test the hypothesis that visual field assessment in ocular disease measured with target stimuli within or close to complete spatial summation results in larger threshold elevation compared to when measured with the standard Goldmann III target size. The hypothesis predicts a greater loss will be identified in ocular disease. Additionally, we sought to develop a theoretical framework that would allow comparisons of thresholds with disease progression when using different Goldmann targets.

METHODS

The Humphrey Field Analyser (HFA) 30-2 grid was used in 13 patients with early/established optic nerve disease using the current Goldmann III target size or a combination of the three smallest stimuli (target size I, II and III). We used data from control subjects at each of the visual field locations for the different target sizes to establish the number of failed points (events) for the patients with optic nerve disease, as well as global indices for mean deviation (MD) and pattern standard deviation (PSD).

RESULTS

The 30-2 visual field testing using alternate target size stimuli showed that all 13 patients displayed more defects (events) compared to the standard Goldmann III target size. The median increase for events was seven additional failed points: (range 1-26). The global indices also increased when the new testing approach was used (MD -3.47 to -6.25 dB and PSD 4.32 to 6.63 dB). Spatial summation mapping showed an increase in critical area (Ac) in disease and overall increase in thresholds when smaller target stimuli were used.

CONCLUSIONS

When compared to the current Goldmann III paradigm, the use of alternate sized targets within the 30-2 testing protocol revealed a greater loss in patients with optic nerve disease for both event analysis and global indices (MD and PSD). We therefore provide evidence in a clinical setting that target size is important in visual field testing.

Incorporating Spatial Models in Visual Field Test Procedures

Purpose

To introduce a perimetric algorithm (Spatially Weighted Likelihoods in Zippy Estimation by Sequential Testing [ZEST] [SWeLZ]) that uses spatial information on every presentation to alter visual field (VF) estimates, to reduce test times without affecting output precision and accuracy.

Methods

SWeLZ is a maximum likelihood Bayesian procedure, which updates probability mass functions at VF locations using a spatial model. Spatial models were created from empirical data, computational models, nearest neighbor, random relationships, and interconnecting all locations. SWeLZ was compared to an implementation of the ZEST algorithm for perimetry using computer simulations on 163 glaucomatous and 233 normal VFs (Humphrey Field Analyzer 24-2). Output measures included number of presentations and visual sensitivity estimates.

Results

There was no significant difference in accuracy or precision of SWeLZ for the different spatial models relative to ZEST, either when collated across whole fields or when split by input sensitivity. Inspection of VF maps showed that SWeLZ was able to detect localized VF loss. SWeLZ was faster than ZEST for normal VFs: median number of presentations reduced by 20% to 38%. The number of presentations was equivalent for SWeLZ and ZEST when simulated on glaucomatous VFs.

Conclusions

SWeLZ has the potential to reduce VF test times in people with normal VFs, without detriment to output precision and accuracy in glaucomatous VFs.

Translational Relevance

SWeLZ is a novel perimetric algorithm. Simulations show that SWeLZ can reduce the number of test presentations for people with normal VFs. Since many patients have normal fields, this has the potential for significant time savings in clinical settings.

The Effect of Cataract on Early Stage Glaucoma Detection Using Spatial and Temporal Contrast Sensitivity Tests

BACKGROUND

To investigate the effect of cataract on the ability of spatial and temporal contrast sensitivity tests used to detect early glaucoma.

METHODS

Twenty-seven glaucoma subjects with early cataract (mean age 60 ± 10.2 years) which constituted the test group were recruited together with twenty-seven controls (cataract only) matched for age and cataract type from a primary eye care setting. Contrast sensitivity to flickering gratings at 20 Hz and stationary gratings with and without glare, were measured for 0.5, 1.5 and 3 cycles per degree (cpd) in central vision. Perimetry and structural measurements with the Heidelberg Retinal Tomograph (HRT) were also performed.

RESULTS

After considering the effect of cataract, contrast sensitivity to stationary gratings was reduced in the test group compared with controls with a statistically significant mean difference of 0.2 log units independent of spatial frequency. The flicker test showed a significant difference between test and control group at 1.5 and 3 cpd (p = 0.019 and p = 0.011 respectively). The percentage of glaucoma patients who could not see the temporal modulation was much higher compared with their cataract only counterparts. A significant correlation was found between the reduction of contrast sensitivity caused by glare and the Glaucoma Probability Score (GPS) as measured with the HRT (p<0.005).

CONCLUSIONS

These findings indicate that both spatial and temporal contrast sensitivity tests are suitable for distinguishing between vision loss as a consequence of glaucoma and vision loss caused by cataract only. The correlation between glare factor and GPS suggests that there may be an increase in intraocular stray light in glaucoma.

Does the Swedish Interactive Threshold Algorithm (SITA) accurately map visual field loss attributed to vigabatrin?

Background

Vigabatrin (VGB) is an anti-epileptic medication which has been linked to peripheral constriction of the visual field. Documenting the natural history associated with continued VGB exposure is important when making decisions about the risk and benefits associated with the treatment. Due to its speed the Swedish Interactive Threshold Algorithm (SITA) has become the algorithm of choice when carrying out Full Threshold automated static perimetry. SITA uses prior distributions of normal and glaucomatous visual field behaviour to estimate threshold sensitivity. As the abnormal model is based on glaucomatous behaviour this algorithm has not been validated for VGB recipients. We aim to assess the clinical utility of the SITA algorithm for accurately mapping VGB attributed field loss.

Methods

The sample comprised one randomly selected eye of 16 patients diagnosed with epilepsy, exposed to VGB therapy. A clinical diagnosis of VGB attributed visual field loss was documented in 44% of the group. The mean age was 39.3 years ± 14.5 years and the mean deviation was -4.76 dB ±4.34 dB. Each patient was examined with the Full Threshold, SITA Standard and SITA Fast algorithm.

Results

SITA Standard was on average approximately twice as fast (7.6 minutes) and SITA Fast approximately 3 times as fast (4.7 minutes) as examinations completed using the Full Threshold algorithm (15.8 minutes). In the clinical environment, the visual field outcome with both SITA algorithms was equivalent to visual field examination using the Full Threshold algorithm in terms of visual inspection of the grey scale plots , defect area and defect severity.

Conclusions

Our research shows that both SITA algorithms are able to accurately map visual field loss attributed to VGB. As patients diagnosed with epilepsy are often vulnerable to fatigue, the time saving offered by SITA Fast means that this algorithm has a significant advantage for use with VGB recipients.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2415-14-166) contains supplementary material, which is available to authorized users.