Modelling series of visual fields to detect progression in normal-tension glaucoma

Validating Trend-Based End Points for Neuroprotection Trials in Glaucoma

Purpose

The purpose of this study was to evaluate the power of trend-based visual field (VF) progression end points against long-term development of event-based end points accepted by the US Food and Drug Administration (FDA).

Methods

One eye from 3352 patients with ≥10 24-2 VFs (median = 11 years) follow-up were analyzed. Two FDA-compatible criteria were applied to these series to label "true-progressed" eyes: ≥5 locations changing from baseline by more than 7 dB (FDA-7) or by more than the expected test-retest variability (GPA-like) in 2 consecutive tests. Observed rates of progression (RoP) were used to simulate trial-like series (2 years) randomly assigned (1000 times) to a "placebo" or a "treatment" arm. We simulated neuroprotective "treatment" effects by changing the proportion of "true progressed" eyes in the two arms. Two trend-based methods for mean deviation (MD) were assessed: (1) linear mixed model (LMM), testing average difference in RoP between the two arms, and (2) time-to-progression (TTP), calculated by linear regression as time needed for MD to decline by predefined cutoffs from baseline. Power curves with 95% confidence intervals were calculated for trend and event-based methods on the simulated series.

Results

The FDA-7 and GPA-like progression was achieved by 45% and 55% of the eyes in the clinical database. LMM and TTP had similar power, significantly superior to the event-based methods, none of which reached 80% power. All methods had a 5% false-positive rate.

Conclusions

The trend-based methods can efficiently detect treatment effects defined by long-term FDA-compatible progression.

Translational Relevance

The assessment of the power of trend-based methods to detect clinically relevant progression end points.

The number of examinations required for the accurate prediction of the progression of the central 10-degree visual field test in glaucoma

The purpose of the study was to investigate the number of examinations required to precisely predict the future central 10-degree visual field (VF) test and to evaluate the effect of fitting non-linear models, including quadratic regression, exponential regression, logistic regression, and M-estimator robust regression model, for eyes with glaucoma. 180 eyes from 133 open angle glaucoma patients with a minimum of 13 Humphrey Field Analyzer 10-2 SITA standard VF tests were analyzed in this study. Using trend analysis with ordinary least squares linear regression (OLSLR), the first, second, and third future VFs were predicted in a point-wise (PW) manner using a varied number of prior VF sequences, and mean absolute errors (MAE) were calculated. The number of VFs needed to reach the minimum 95% confidence interval (CI) of the MAE of the OLSLR was investigated. We also examined the effect of applying other non-linear models. When predicting the first, second, and third future VFs using OLSLR, the minimum MAE was obtained using VF1-12 (2.15 ± 0.98 dB), VF1-11 (2.33 ± 1.10 dB), and VF1-10 (2.63 ± 1.36 dB), respectively. To reach the 95% CI of these MAEs, 10, 10, and 8 VFs were needed for the first, second and third future VF predictions, respectively. No improvement was observed by applying non-linear regression models. As a conclusion, approximately 8-10 VFs were needed to achieve an accurate prediction of PW VF sensitivity of the 10-degree central VF.

The Usefulness of Assessing Glaucoma Progression With Postprocessed Visual Field Data

Purpose

Data postprocessing with statistical techniques that are less sensitive to noise can be used to reduce variability in visual field (VF) series. We evaluated the detection of glaucoma progression with postprocessed VF data generated with the dynamic structure–function (DSF) model and MM-estimation robust regression (MRR).

Method

The study included 118 glaucoma eyes with at least 15 visits selected from the Rotterdam dataset. The DSF and MRR models were each applied to observed mean deviation (MD) values from the first three visits (V_1–3) to predict the MD at V_4. MD at V₅ was predicted with data from V_1–4 and so on until the MD at V₉ was predicted, creating two additional datasets: DSF-predicted and MRR-predicted. Simple linear regression was performed to assess progression at the ninth visit. Sensitivity was evaluated by adjusting for false-positive rates estimated from patients with stable glaucoma and by using longer follow-up series (12th and 15th visits) as a surrogate for progression.

Results

For specificities of 80% to 100%, the DSF-predicted dataset had greater sensitivity than the observed and MRR-predicted dataset when positive rates were normalized with corresponding false-positive estimates. The DSF-predicted and observed datasets had similar sensitivity when the surrogate reference standard was applied.

Conclusions

Without compromising specificity, the use of DSF-predicted measurements to identify progression resulted in a better or similar sensitivity compared to using existing VF data.

Translational Relevance

The DSF model could be applied to postprocess existing visual field data, which could then be evaluated to identify patients at risk of progression.

Rates of Visual Field Change in Patients With Glaucoma and Healthy Individuals: Findings From a Median 25-Year Follow-up

Importance

Estimating the rate of glaucomatous visual field change provides practical assessment of disease progression and has implications for management decisions.

Objective

To assess the rates of visual field change in patients receiving treatment for glaucoma compared with healthy individuals over an extensive follow-up period and to quantify the impact of important covariates for these rates.

Design, Setting, and Participants

This prospective longitudinal cohort study was conducted in a hospital-based setting from January 1991 to February 2020. The study included 40 patients receiving treatment for open-angle glaucoma and 29 healthy participants. One eye of each participant was randomly selected as the study eye.

Exposures

Patients with glaucoma and healthy participants received testing with standard automated perimetry every 6 months. Individual rates of mean sensitivity change were computed using ordinary least-squares regression analysis, and linear mixed-effects modeling was used to estimate the mean rates of mean sensitivity change in the 2 groups and the impact of baseline mean sensitivity, baseline age, and follow-up intraocular pressure for rate estimates.

Main Outcomes and Measures

Rate of mean sensitivity change in patients with glaucoma and healthy participants.

Results

A total of 40 patients with glaucoma (median age, 53.07 years [IQR, 48.34-57.97 years]; 21 men [52%]) and 29 healthy participants (median age, 48.80 years [IQR, 40.40-59.07 years], 17 women [59%]) were followed up for a median of 25.65 years (IQR, 22.49-27.02 years) and 19.56 years (IQR, 16.19-26.21 years), respectively. Most participants (65 individuals [94%]) self-identified as White, with the exception of 2 patients with glaucoma (1 self-identified as Black and 1 as South Asian) and 2 healthy participants (both self-identified as South Asian). The mean follow-up intraocular pressure of patients with glaucoma (median, 15.83 mm Hg [IQR, 13.05-17.33 mm Hg]) was similar to that of healthy participants (median, 14.94 mm Hg [IQR, 13.28-16.01 mm Hg]; P = .25). In an ordinary least-squares regression analysis, 31 patients (78%) with glaucoma had rates of mean sensitivity change within the range of healthy participants (ie, between -0.20 dB/y and 0.15 dB/y). Linear mixed-effects modeling revealed that the mean (SE) rate of mean sensitivity change in healthy participants was 0.003 (0.033) dB/y (95% CI, -0.062 to 0.068; P = .93). In comparison, patients with glaucoma had a mean (SE) rate of mean sensitivity change that was -0.032 (0.052) dB/y faster, but this difference was not statistically significant (95% CI, -0.134 to 0.070; P = .53). Among covariates, only baseline mean sensitivity was associated with the rate of mean sensitivity change (mean [SE], 0.021 [0.010] dB/y/dB; 95% CI, 0.002-0.041; P = .03).

Conclusions and Relevance

The results of this cohort study suggest that over a median follow-up of more than 25 years, the rate of visual field change in patients receiving treatment for glaucoma was comparable to that of healthy individuals. These findings could guide practitioners in making management decisions.

Augmenting Kalman Filter Machine Learning Models with Data from OCT to Predict Future Visual Field Loss: An Analysis Using Data from the African Descent and Glaucoma Evaluation Study and the Diagnostic Innovation in Glaucoma Study

Purpose

To assess whether the predictive accuracy of machine learning algorithms using Kalman filtering for forecasting future values of global indices on perimetry can be enhanced by adding global retinal nerve fiber layer (RNFL) data and whether model performance is influenced by the racial composition of the training and testing sets.

Design

Retrospective, longitudinal cohort study.

Participants

Patients with open-angle glaucoma (OAG) or glaucoma suspects enrolled in the African Descent and Glaucoma Evaluation Study or Diagnostic Innovation in Glaucoma Study.

Methods

We developed a Kalman filter (KF) with tonometry and perimetry data (KF-TP) and another KF with tonometry, perimetry, and global RNFL data (KF-TPO), comparing these models with one another and with 2 linear regression (LR) models for predicting mean deviation (MD) and pattern standard deviation values 36 months into the future for patients with OAG and glaucoma suspects. We also compared KF model performance when trained on individuals of European and African descent and tested on patients of the same versus the other race.

Main Outcome Measures

Predictive accuracy (percentage of MD values forecasted within the 95% repeatability interval) differences among the models.

Results

Among 362 eligible patients, the mean ± standard deviation age at baseline was 71.3 ± 10.4 years; 196 patients (54.1%) were women; 202 patients (55.8%) were of European descent, and 139 (38.4%) were of African descent. Among patients with OAG (n = 296), the predictive accuracy for 36 months in the future was higher for the KF models (73.5% for KF-TP, 71.2% for KF-TPO) than for the LR models (57.5%, 58.0%). Predictive accuracy did not differ significantly between KF-TP and KF-TPO (P = 0.20). If the races of the training and testing set patients were aligned (versus nonaligned), the mean absolute prediction error of future MD improved 0.39 dB for KF-TP and 0.48 dB for KF-TPO.

Conclusions

Adding global RNFL data to existing KFs minimally improved their predictive accuracy. Although KFs attained better predictive accuracy when the races of the training and testing sets were aligned, these improvements were modest. These findings will help to guide implementation of KFs in clinical practice.

The glaucoma intensive treatment study: interim results from an ongoing longitudinal randomized clinical trial

PURPOSE

The aim of the study was to determine the perimetric rate of glaucoma progression in the ongoing Glaucoma Intensive Treatment Study (GITS) after 3 years of follow-up.

DESIGN

This is a randomized, two-centre, prospective open-labelled treatment trial for open-angle glaucoma (OAG).

PARTICIPANTS

The participants of this study were treatment-naive patients with newly diagnosed OAG, aged 46-78 years, with early to moderate glaucomatous visual field loss scheduled to be followed for 5 years within the study.

METHODS

Patients were randomized to initial treatment with either topical monotherapy or with an intensive approach using drugs from three different classes, plus 360° laser trabeculoplasty. Changes in treatment were allowed. Standard automated perimetry and tonometry were performed and side-effects documented. All results are presented using intention-to-treat analysis.

RESULTS

A total of 242 patients were randomized. After 3 years of follow-up, eight patients were lost to follow-up, six of whom were deceased. The median untreated baseline intraocular pressure (IOP) was 24 mmHg in both arms. The median IOP was almost constant over the 3 years of follow-up: ≈17 mmHg in the mono-arm and ≈14 mmHg in the multi-treatment arm. Treatment was intensified in 42% of the mono-treated patients and in 7% of the multi-treated patients. Treatment was reduced in 13% of the multi-treated patients. The median perimetric rate of progression was -0.5%/year in the mono-treated group and -0.1%/year in the multi-treated group (p = 0.03).

CONCLUSION

The rate of disease progression was significantly slower in the multi-treated patients than in the mono-treated patients. Further follow-up will show whether this difference is sustained over time.

Detecting Progression of Retinitis Pigmentosa Using the Binomial Pointwise Linear Regression Method

Purpose

A method of evaluating central visual field (VF) progression in eyes with retinitis pigmentosa (RP) has still to be established. We previously reported the potential merit of applying a binomial test to pointwise linear regression (binomial PLR) in glaucoma progression. In the current study, we investigated the usefulness of binomial PLR in eyes with RP.

Methods

A series of 10 VFs (VF 1–10, Humphrey field analyzer, 10-2 test) from 196 eyes of 103 patients with RP were collected retrospectively. The PLR was performed by regressing the total deviation of all test points with the complete series of 10 VFs. The accuracy (positive predictive value, negative predictive value, and false-positive rate) and the time required to detect VF progression with shorter VF series (from VF 1–5 to VF 1–9) were compared across the binomial PLR, a permutation analysis of PLR (PoPLR), and a mean deviation (MD) trend analysis.

Results

In evaluating VF progression, the binomial PLR was comparable with the PoPLR and MD trend analyses in its positive predictive value (0.55 to 0.95), negative predictive value (0.67 to 0.92), and false-positive rate (0.01 to 0.05). The binomial PLR required significantly less time to detect VF progression (5.0 ± 2.0 years) than the PoPLR and MD trend analyses (P < 0.01, P < 0.001, respectively).

Conclusions

The application of a binomial PLR achieved reliable and earlier detection of central VF progression in eyes with RP.

Translational Relevance

A binomial PLR was useful in assessing VF progression in RP.

If we don't change direction soon, we'll end up where we're going: a description of the SSY Engine

Data presented during the first two decades of this millennium has shed valuable light on how the intraocular pressure (IOP) is linked to glaucomatous progression. Large prospective controlled trials have confirmed that there is a correlation between the change in intraocular pressure (IOP) and the risk for visual field progression. The magnitude of the effect, as indicated by these studies, is a 10-15% decrease in risk for a 1 mmHg drop in IOP. The risk is correlated with the rate at which patients develops field loss, that is the Rate of Progression or RoP, which in turn makes future projections of a patient's progression over time at a given IOP level a reasonable possibility. This led to the creation of the SSY (Save Sight Years) concept and later the SSY engine, which is a practical application of this model in the form of a web application. This article describes the thinking behind this system, how it works, the caveats and where we think it can benefit clinical practice.

Predicting eyes at risk for rapid glaucoma progression based on an initial visual field test using machine learning

OBJECTIVE

To assess whether machine learning algorithms (MLA) can predict eyes that will undergo rapid glaucoma progression based on an initial visual field (VF) test.

DESIGN

Retrospective analysis of longitudinal data.

SUBJECTS

175,786 VFs (22,925 initial VFs) from 14,217 patients who completed ≥5 reliable VFs at academic glaucoma centers were included.

METHODS

Summary measures and reliability metrics from the initial VF and age were used to train MLA designed to predict the likelihood of rapid progression. Additionally, the neural network model was trained with point-wise threshold data in addition to summary measures, reliability metrics and age. 80% of eyes were used for a training set and 20% were used as a test set. MLA test set performance was assessed using the area under the receiver operating curve (AUC). Performance of models trained on initial VF data alone was compared to performance of models trained on data from the first two VFs.

MAIN OUTCOME MEASURES

Accuracy in predicting future rapid progression defined as MD worsening more than 1 dB/year.

RESULTS

1,968 eyes (8.6%) underwent rapid progression. The support vector machine model (AUC 0.72 [95% CI 0.70-0.75]) most accurately predicted rapid progression when trained on initial VF data. Artificial neural network, random forest, logistic regression and naïve Bayes classifiers produced AUC of 0.72, 0.70, 0.69, 0.68 respectively. Models trained on data from the first two VFs performed no better than top models trained on the initial VF alone. Based on the odds ratio (OR) from logistic regression and variable importance plots from the random forest model, older age (OR: 1.41 per 10 year increment [95% CI: 1.34 to 1.08]) and higher pattern standard deviation (OR: 1.31 per 5-dB increment [95% CI: 1.18 to 1.46]) were the variables in the initial VF most strongly associated with rapid progression.

CONCLUSIONS

MLA can be used to predict eyes at risk for rapid progression with modest accuracy based on an initial VF test. Incorporating additional clinical data to the current model may offer opportunities to predict patients most likely to rapidly progress with even greater accuracy.

The usefulness of the Deep Learning method of variational autoencoder to reduce measurement noise in glaucomatous visual fields

The aim of the study was to investigate the usefulness of processing visual field (VF) using a variational autoencoder (VAE). The training data consisted of 82,433 VFs from 16,836 eyes. Testing dataset 1 consisted of test-retest VFs from 104 eyes with open angle glaucoma. Testing dataset 2 was series of 10 VFs from 638 eyes with open angle glaucoma. A VAE model to reconstruct VF was developed using the training dataset. VFs in the testing dataset 1 were then reconstructed using the trained VAE and the mean total deviation (mTD) was calculated (mTDVAE). In testing dataset 2, the mTD value of the tenth VF was predicted using shorter series of VFs. A similar calculation was carried out using a weighted linear regression where the weights were equal to the absolute difference between mTD and mTDVAE. In testing dataset 1, there was a significant relationship between the difference between mTD and mTDVAE from the first VF and the difference between mTD in the first and second VFs. In testing dataset 2, mean squared prediction errors with the weighted mTD trend analysis were significantly smaller than those form the unweighted mTD trend analysis.

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.

Validating the efficacy of the binomial pointwise linear regression method to detect glaucoma progression with multicentral database

BACKGROUND/AIM

We previously reported the benefit of applying binomial pointwise linear regression (PLR: binomial PLR) to detect 10-2 glaucomatous visual field (VF) progression. The purpose of the current study was to validate the usefulness of the binomial PLR to detect glaucomatous VF progression in the central 24°.

METHODS

Series of 15 VFs (Humphrey Field Analyzer 24-2 SITA-standard) from 341 eyes of 233 patients, obtained over 7.9±2.1 years (mean±SD), were investigated. PLR was performed by regressing the total deviation of all test points. VF progression was determined from the VF test points analyses using the binomial test (one side, p<0.025). The time needed to detect VF progression was compared across the binomial PLR, permutation analysis of PLR (PoPLR) and mean total deviation (mTD) trend analysis.

RESULTS

The binomial PLR was comparable with PoPLR and mTD trend analyses in the positive predictive value (0.18-0.87), the negative predictive value (0.89-0.95) and the false positive rate (0.057-0.35) to evaluate glaucomatous VF progression. The time to classify progression with binomial PLR (5.8±2.8 years) was significantly shorter than those with mTD trend analysis (6.7±2.8 years) and PoPLR (6.6±2.7 years).

CONCLUSIONS

The binomial PLR method, which detected glaucomatous VF progression in the central 24° significantly earlier than PoPLR and mTD trend analyses, shows promise for improving our ability to detect visual field progression for clinical management of glaucoma and in clinical trials of new glaucoma therapies.

Visual Field Prediction using Recurrent Neural Network

Artificial intelligence capabilities have, recently, greatly improved. In the past few years, one of the deep learning algorithms, the recurrent neural network (RNN), has shown an outstanding ability in sequence labeling and prediction tasks for sequential data. We built a reliable visual field prediction algorithm using RNN and evaluated its performance in comparison with the conventional pointwise ordinary linear regression (OLR) method. A total of 1,408 eyes were used as a training dataset and another dataset, comprising 281 eyes, was used as a test dataset. Five consecutive visual field tests were provided to the constructed RNN as input and a 6^th visual field test was compared with the output of the RNN. The performance of the RNN was compared with that of OLR by predicting the 6^th visual field in the test dataset. The overall prediction performance of RNN was significantly better than OLR. The pointwise prediction error of the RNN was significantly smaller than that of the OLR in most areas known to be vulnerable to glaucomatous damage. The RNN was also more robust and reliable regarding worsening in the visual field examination. In clinical practice, the RNN model can therefore assist in decision-making for further treatment of 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.

Using Kalman Filtering to Forecast Disease Trajectory for Patients With Normal Tension Glaucoma

PURPOSE

To determine whether a machine learning technique called Kalman filtering (KF) can accurately forecast future values of mean deviation (MD), pattern standard deviation, and intraocular pressure for patients with normal tension glaucoma (NTG).

DESIGN

Development and testing of a forecasting model for glaucoma progression.

METHODS

We parameterized and validated a KF (KF-NTG) to forecast MD, pattern standard deviation, and intraocular pressure at 24 months into the future using 263 eyes of 263 Japanese patients with NTG. We determined the proportion of patients with MD forecasts within 0.5, 1.0, and 2.5 dBs of the actual values and calculated the root mean squared error (RMSE) for each forecast. We compared KF-NTG with a previously published KF model calibrated using patients with high-tension open-angle glaucoma (KF-HTG) and to 3 conventional forecasting algorithms.

RESULTS

The 263 patients with NTG had mean ± standard deviation age of 63.4 ± 10.5 years. KF-NTG forecasted MD values 24 months ahead within 0.5, 1.0, and 2.5 dBs of the actual value for 78 eyes (32.2%), 122 eyes (50.4%), and 211 eyes (87.2%), respectively. The proportion of eyes with MD values forecasted within 2.5 dB of the actual value for the KF-NTG (87.2%) were similar to KF-HTG (86.0%) and the null model (86.4%), and much better than the 2 linear regression-based models (72.7-74.0%; P < .001). When forecasting MD, KF-NTG (RMSE = 2.71) and KF-HTG (RMSE = 2.68) achieved lower RMSE than the other 3 forecasting models (RMSE = 2.81-3.90), indicating better performance.

CONCLUSION

As observed previously for patients with HTG, KF can also effectively forecast disease trajectory for many patients with NTG.

Early Detection of Glaucomatous Visual Field Progression Using Pointwise Linear Regression With Binomial Test in the Central 10 Degrees

PURPOSE

We previously reported that it was beneficial to apply binomial pointwise linear regression (PLR) to detect 24-2 glaucomatous visual field (VF) progression, compared to mean deviation (MD) trend analysis and permutation analysis of PLR (PoPLR). The purpose of the current study was to validate the usefulness of the binomial PLR method to detect VF progression in the central 10 degrees in glaucoma patients.

DESIGN

Reliability assessment.

METHODS

A series of 15 VFs (Humphrey Field Analyzer 10-2 SITA-standard) from 97 eyes in 69 primary open-angle glaucoma patients, obtained over 8.5 ± 1.3 years (mean ± SD), were investigated. PLR was performed by regressing the total deviation of all test points on the series of 15 VFs. VF progression was determined from the analyses of VF test points using the binomial test (1-sided, P < .025). The time needed to detect VF progression was also investigated. The results were compared with PoPLR and MD trend analyses.

RESULTS

The binomial PLR was comparable to PoPLR and MD trend analyses in the positive predictive value (0.19 to 0.80), the negative predictive value (0.86 to 1.0), and the false positive rate (0.0 to 0.13) to evaluate glaucomatous VF progression. The time needed to detect VF progression (4.2 ± 1.8 years) was significantly shorter with the binomial PLR method compared with PoPLR and MD trend analysis (P = .04, P = .012, respectively).

CONCLUSIONS

The binomial PLR method detected glaucomatous VF progression in the central 10 degrees significantly earlier than PoPLR and MD trend analyses.

The Glaucoma Intensive Treatment Study (GITS), a randomized clinical trial: design, methodology and baseline data

PURPOSE

The primary objective of the ongoing Glaucoma Intensive Treatment Study (GITS) is to evaluate the effectiveness of immediate intensive treatment in comparison with the commonly recommended stepped regimen on the predicted visual field. The two treatment arms are also being compared regarding quality of life (QoL), intraocular pressure (IOP) reduction, frequency of reported side-effects, adverse events and adherence to prescribed treatment.

DESIGN

A randomized, two-centre, prospective open-labelled treatment trial for open-angle glaucoma.

PARTICIPANTS

Individuals aged 40-78 years with previously untreated and newly diagnosed glaucoma with early to moderate visual field loss were eligible.

METHODS

Patients were randomized to initial treatment either using drug monotherapy in accordance with common glaucoma guidelines or using a more intensive approach including eyedrops containing drugs from three different classes combined with 360° laser trabeculoplasty. The patients are to be followed for 5 years at visits including standard automated perimetry, optical coherence tomography (OPT) and tonometry. Change of treatment is allowed and decided upon jointly with the patient as in conventional glaucoma management.

MAIN OUTCOME

The estimated predicted preserved visual field and QoL at end of expected lifetime.

RESULTS

A total of 242 patients, 45% females, mean age 68 years, were randomized. The median untreated IOP was 24 mm Hg, and the median visual field index (VFI), indicating the percentage of a full field, was 92%.

CONCLUSION

Glaucoma Intensive Treatment Study is a clinical trial in which two groups of patients randomized to different initial intensities of IOP-reducing treatment are being compared with regard to rate of visual field progression and prediction of serious glaucomatous visual field loss at estimated at end of life.

Treatment of Advanced Glaucoma Study: a multicentre randomised controlled trial comparing primary medical treatment with primary trabeculectomy for people with newly diagnosed advanced glaucoma-study protocol

BACKGROUND

Presentation with advanced glaucoma is the major risk factor for lifetime blindness. Effective intervention at diagnosis is expected to minimise risk of further visual loss in this group of patients.

AIM

To compare clinical and cost-effectiveness of primary medical management compared with primary surgery for people presenting with advanced open-angle glaucoma (OAG).

METHODS

Design: A prospective, pragmatic multicentre randomised controlled trial (RCT).

SETTING

Twenty-seven UK hospital eye services.

PARTICIPANTS

Four hundred and forty patients presenting with advanced OAG, according to the Hodapp-Parish-Anderson classification of visual field loss.

INTERVENTION

Participants will be randomised to medical treatment or augmented trabeculectomy (1:1 allocation minimised by centre and presence of advanced disease in both eyes).

MAIN OUTCOME MEASURES

The primary outcome is vision-related quality of life measured by the National Eye Institute-Visual Function Questionnaire-25 at 24 months. Secondary outcomes include generic EQ-5D-5L, Health Utility Index-3 and glaucoma-related health status (Glaucoma Utility Index), patient experience, visual field measured by mean deviation value, logarithm of the mean angle of resolution visual acuity, intraocular pressure, adverse events, standards for driving and eligibility for blind certification. Incremental cost per quality-adjusted life-year (QALY) based on EQ-5D-5L and glaucoma profile instrument will be estimated.

RESULTS

The study will report the comparative effectiveness and cost-effectiveness of medical treatment against augmented trabeculectomy in patients presenting with advanced glaucoma in terms of patient-reported health and visual function, clinical outcomes and incremental cost per QALY at 2 years.

CONCLUSIONS

Treatment of Advanced Glaucoma Study will be the first RCT reporting outcomes from the perspective of those with advanced glaucoma.

TRIAL REGISTRATION NUMBER

ISRCTN56878850, Pre-results.

A New Graphical Tool for Assessing Visual Field Progression in Clinical Populations

Purpose

We demonstrate a new approach for assessing and visualizing visual field (VF) progression in clinics.

Methods

Two summary measures for VF progression, Rate of Progression (RP) and Loss of Sight Years (LSY), are combined with a novel visualization (Hedgehog Plots). RP is calculated per eye using linear regression of mean deviation (MD) against time of follow-up. LSY is a novel parameter, linked to actuarial data, which estimates the number of years that a patient will have advanced bilateral VF loss in their predicted remaining lifetime. Every eye is given a rank within the sample based on RP and LSY allowing for “priority” patients to be identified. We illustrate differences between the parameters with an experiment comparing the cases flagged as “priority” by each method using data from 1263 VF records.

Results

RP for every eye in a “clinic” can be visualized and assessed using a Hedgehog Plot. Eyes are ranked against all other eyes by RP and LSY; these parameters provide different and complementary information on a patient's VF progression status. A purpose written interactive application demonstrating the techniques is available in the public domain at https://crabblab.shinyapps.io/hedgehog.

Conclusion

Hedgehog Plots provide a tool for visualizing VF progression in groups of patients and can be used potentially to prioritize monitoring resources.

Translational Relevance

This study illustrates a novel visualization technique and an interactive application that can be used to help determine VF progression in large groups of patients.

Bayesian hierarchical modeling of longitudinal glaucomatous visual fields using a two-stage approach

The Bayesian approach has become increasingly popular because it allows to fit quite complex models to data via Markov chain Monte Carlo sampling. However, it is also recognized nowadays that Markov chain Monte Carlo sampling can become computationally prohibitive when applied to a large data set. We encountered serious computational difficulties when fitting an hierarchical model to longitudinal glaucoma data of patients who participate in an ongoing Dutch study. To overcome this problem, we applied and extended a recently proposed two-stage approach to model these data. Glaucoma is one of the leading causes of blindness in the world. In order to detect deterioration at an early stage, a model for predicting visual fields (VFs) in time is needed. Hence, the true underlying VF progression can be determined, and treatment strategies can then be optimized to prevent further VF loss. Because we were unable to fit these data with the classical one-stage approach upon which the current popular Bayesian software is based, we made use of the two-stage Bayesian approach. The considered hierarchical longitudinal model involves estimating a large number of random effects and deals with censoring and high measurement variability. In addition, we extended the approach with tools for model evaluation. Copyright © 2017 John Wiley & Sons, Ltd.

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.

The retest distribution of the visual field summary index mean deviation is close to normal

PURPOSE

When modelling optimum strategies for how best to determine visual field progression in glaucoma, it is commonly assumed that the summary index mean deviation (MD) is normally distributed on repeated testing. Here we tested whether this assumption is correct.

METHODS

We obtained 42 reliable 24-2 Humphrey Field Analyzer SITA standard visual fields from one eye of each of five healthy young observers, with the first two fields excluded from analysis. Previous work has shown that although MD variability is higher in glaucoma, the shape of the MD distribution is similar to that found in normal visual fields. A Shapiro-Wilks test determined any deviation from normality. Kurtosis values for the distributions were also calculated.

RESULTS

Data from each observer passed the Shapiro-Wilks normality test. Bootstrapped 95% confidence intervals for kurtosis encompassed the value for a normal distribution in four of five observers. When examined with quantile-quantile plots, distributions were close to normal and showed no consistent deviations across observers.

CONCLUSIONS

The retest distribution of MD is not significantly different from normal in healthy observers, and so is likely also normally distributed - or nearly so - in those with glaucoma. Our results increase our confidence in the results of influential modelling studies where a normal distribution for MD was assumed.

Neuroretinal Rim Area Change in Glaucoma Patients With Visual Field Progression Endpoints and Intraocular Pressure Reduction. The Canadian Glaucoma Study: 4

PURPOSE

To compare rim area rates in patients with and without the visual field (VF) progression endpoint in the Canadian Glaucoma Study and determine whether intraocular pressure (IOP) reduction following the endpoint altered rim area rate.

DESIGN

Prospective multicenter cohort study.

METHODS

setting: University hospitals.

PATIENT POPULATION

Two hundred and six patients with open-angle glaucoma were examined at 4-month intervals with standard automated perimetry and confocal scanning laser tomography.

INTERVENTION

After the endpoint, IOP was reduced by ≥20%.

OUTCOME MEASURES

Univariate analysis for change in rim area rate and multivariable analysis to adjust for independent covariates (eg, age, sex, and IOP).

RESULTS

Patients with an endpoint (n = 59) had a worse rim area rate prior to the endpoint compared to those without (n = 147; median [interquartile range]: -14 [-32, 11] × 10(-3) mm(2)/y and -5 [-14, 5] × 10(-3) mm(2)/y, respectively, P = .02). In univariate analysis, there was no difference in rim area rate before and after the endpoint (median difference [95% CI], 8 (-10, 24) × 10(-3) mm(2)/y), but the muItivariate analysis showed that IOP reduction >2 mm Hg after the endpoint was strongly linked to a reduction in rim area rate decline (8 × 10(-3) mm(2)/y for each additional 1 mm Hg reduction).

CONCLUSIONS

Patients with a VF endpoint had a median rim area rate that was nearly 3 times worse than those without an endpoint. Lower mean follow-up IOP was independently associated with a slower decline in rim area.

Comparison of Snellen and Early Treatment Diabetic Retinopathy Study charts using a computer simulation

AIM

To compare accuracy, reproducibility and test duration for the Snellen and the Early Treatment Diabetic Retinopathy Study (ETDRS) charts, two main tools used to measure visual acuity (VA).

METHODS

A computer simulation was programmed to run multiple virtual patients, each with a unique set of assigned parameters, including VA, false-positive and false-negative error values. For each virtual patient, assigned VA was randomly chosen along a continuous scale spanning the range between 1.0 to 0.0 logMAR units (equivalent to 20/200 to 20/20). Each of 30 000 virtual patients were run ten times on each of the two VA charts.

RESULTS

Average test duration (expressed as the total number of characters presented during the test ±SD) was 12.6±11.1 and 31.2±14.7 characters, for the Snellen and ETDRS, respectively. Accuracy, defined as the absolute difference (± SD) between the assigned VA and the measured VA, expressed in logMAR units, was superior in the ETDRS charts: 0.12±0.14 and 0.08±0.08, for the Snellen and ETDRS charts, respectively. Reproducibility, expressed as test-retest variability, was superior in the ETDRS charts: 0.23±0.17 and 0.11±0.09 logMAR units, for the Snellen and ETDRS charts, respectively.

CONCLUSION

A comparison of true (assigned) VA to measured VA, demonstrated, on average, better accuracy and reproducibility of the ETDRS chart, but at the penalty of significantly longer test duration. These differences were most pronounced in the low VA range. The reproducibility using a simulation approach is in line with reproducibility values found in several clinical studies.

Targeted spatial sampling using GOANNA improves detection of visual field progression

PURPOSE

A new automated visual field testing approach that samples scotoma edges at a finer spatial resolution, GOANNA (Gradient-Oriented Automated Natural Neighbour Approach) was previously shown to improve accuracy and precision around those regions compared to current procedures in computer simulation. The purpose of this study was to observe if this improvement translated to more accurate classification of glaucomatous progression.

METHODS

Computer simulations were undertaken on six procedures: three variants of GOANNA on 150 locations; two variants of ZEST on 52 locations; and the ideal case where true thresholds are perfectly measured. The median number of presentations of GOANNA was matched to ZEST. The procedures were run on 156 sequences of simulated progressing fields and 156 sequences of stable fields to determine sensitivity and specificity using point-wise linear regression. Reliable (0% FP, 0% FN) and typical false positive (15% FP, 3% FN) response error conditions were investigated. Area under ROC curves (AUC) were plotted against the number of visual fields acquired to evaluate the performance of these procedures.

RESULTS

The GOANNA framework exhibited equal or greater AUC than ZEST at all visits when baseline fields were initially defective (under both response error conditions) and when baseline fields were initially healthy when no false responses were made. Retest implementations of GOANNA exhibited an improvement over the original GOANNA after the first seven visits when fields were initially healthy.

CONCLUSION

The results suggest that the improvement in precision and accuracy around scotoma borders seen in the GOANNA framework translates to earlier and more accurate detection of progressing fields compared with ZEST, especially in the early stages of glaucomatous progression.

Nonlinear Trend Analysis of Longitudinal Pointwise Visual Field Sensitivity in Suspected and Early Glaucoma

PURPOSE

We have shown previously that a nonlinear exponential model fits longitudinal series of mean deviation (MD) better than a linear model. This study extends that work to investigate the mode (linear versus nonlinear) of change for pointwise sensitivities.

METHODS

Data from 475 eyes of 244 clinically managed participants were analyzed. Sensitivity estimates at each test location were fitted using two-level linear and nonlinear mixed effects models. Sensitivity on the last test date was forecast using a model fit from the earlier test dates in the series. The means of the absolute prediction errors were compared to assess accuracy, and the root means square (RMS) of the prediction errors were compared to assess precision.

RESULTS

Overall, the exponential model provided a significantly better fit (P < 0.05) to the data at the majority of test locations (69%). The exponential model fitted the data significantly better at 85% of locations in the upper hemifield and 58% of locations in the lower hemifield. The rate of visual field (VF) deterioration in the upper hemifield was more rapid (mean, -0.21 dB/y; range, -0.28 to -0.13) than in the lower hemifield (mean, -0.14 dB/y; range, -0.2 to -0.09).

CONCLUSIONS

An exponential model may more accurately track pointwise VF change, at locations damaged by glaucoma. This was more noticeable in the upper hemifield where the VF changed more rapidly. However, linear and exponential models were similar in their ability to forecast future VF status.

TRANSLATIONAL RELEVANCE

The VF progression appears to accelerate in early glaucoma patients.

Comparison of regression models for serial visual field analysis

PURPOSE

Our aim was to compare fit and predictive performance effectiveness of four pointwise regression models in measuring the visual field (VF) decay rate of progression in patients with open-angle glaucoma.

METHODS

We selected Humphrey VF data of patients with open-angle glaucoma with a minimum follow-up time of 6 years. For each eye (n = 798 from 588 patients), we regressed threshold sensitivity (y) at each VF test location for the entire VF series against follow-up time (x), with four candidate first-order regression models: (1) ordinary least-squares linear regression model (y = β 0 + β 1 x); (2) nondecay exponential regression model (y = β 0 + β 1e (x) ); (3) decay exponential regression model ([Formula: see text]); (4) Tobit-censored, maximum-likelihood linear regression model (y* = [Formula: see text], ε ~ N(0, σ(2))), where x is follow-up time and y is threshold sensitivity.

RESULTS

The average [± standard deviation (SD)] baseline VF mean deviation (MD) was -8.2 (±5.5) dB, the mean follow-up was 8.7 (±1.9) years, and the number of follow-up VFs was 14.7 (±4.4). The decay exponential model was the best-fitting (42.7 % of locations) and best-forecasting (65.5 % of locations) model. The decay exponential model was the best prediction model in all categories of severity.

CONCLUSIONS

It is not clear that the ordinary least-squares linear regression model is always the favored model for fitting and forecasting VF data in patients with glaucoma. The pointwise decay exponential regression (PER) model was the best-fitting and best-predicting model across a wide range of glaucoma severity and can be readily understood by clinicians.

Reducing variability in visual field assessment for glaucoma through filtering that combines structural and functional information

PURPOSE

To reduce variability and improve measurements of true change signal in visual field (VF) assessments through the use of filters that combine functional and structural test results.

METHODS

Humphrey VF data (Swedish Interactive Thresholding Algorithm [SITA] Standard, 24-2) and confocal scanning laser ophthalmoscopy (Heidelberg Retina Tomograph [HRT]) data from 1057 eyes of 637 participants were used to derive a filter. Another dataset, consisting of VF and HRT data from 112 eyes of 62 participants each with ≥5 visits, was used to test the filter. At each VF location per eye, the trend over time was modeled by a linear model (LM), and a nonlinear model (NLM), using filtered or unfiltered data, but with the last visit excluded. The SD of residuals from the trends, and prediction errors (PE) for the last visit were compared between filtered and unfiltered data. The filter was reconstructed and analyses were repeated after truncating VF data so that thresholds < 19 dB were replaced by 19 dB to reduce noise.

RESULTS

The SD of the residuals at all 52 VF locations for all analyses was reduced by filtering (P < 0.001). The PE was reduced by filtering at 43 and 47 VF locations (P < 0.05) for LM analyses on observed and truncated data, and all 52 VF locations (P < 0.05) for both NLM analyses. Truncating data before filtering reduced variability (P < 0.01) at 41 and 40 VF locations for LM and NLM analyses.

CONCLUSIONS

Filtering can reduce variability about trends in longitudinal sequences of VF data, and improves the accuracy of predicting the next test result.

The impact of surgical intraocular pressure reduction on visual function using various criteria to define visual field progression

PURPOSE

To examine the impact of surgical intraocular pressure (IOP) reduction on visual function using various methods to define visual field (VF) progression.

METHODS

A retrospective chart review was conducted on consecutive glaucoma patients who underwent surgical IOP reduction between January 1, 2002 and December 31, 2007. All subjects had glaucomatous optic neuropathy, a minimum of 5 preoperative and 5 postoperative VFs, and were followed for a minimum of 2 years both before and after surgery. VF progression was determined using guided progression analysis, linear regression analysis of the visual field index, and individual sensitivity values using Progressor software.

RESULTS

Seventeen eyes of 17 patients (mean age 77.9±9.9 y) were enrolled. Subjects were followed for a mean 5.8±2.4 years before surgery and 4.5±1.5 years after surgery. The mean postoperative IOP (11.3±4.2 mm Hg) and medications (1.3±1.3) were significantly (P<0.001 and P=0.01) reduced compared with before surgery (18.0±3.9 mm Hg, 2.4±0.9, respectively). The number of eyes judged to have VF progression using any method during the postoperative period (3 of 17, 17.6%) was significantly (P=0.03) reduced compared with the preoperative period (9 of 17 eyes, 52.9%). Using visual field index criteria, 8 eyes were judged to have preoperative VF progression and 1 eye had persistent VF progression during the postoperative period. None of the eyes judged to have preoperative VF progression using Early Manifest Glaucoma Trial (n=4) and Progressor criteria (n=1) demonstrated persistent VF progression during the postoperative period. Among eyes with preoperative VF progression, the postoperative slope of mean deviation (-0.21±0.23 dB/y) was significantly (P=0.03) reduced compared with before surgery (-1.01±0.23 dB/y).

CONCLUSIONS

Despite differences in the criteria used to define VF progression, glaucoma surgical IOP reduction significantly reduces the incidence and rate of VF progression.

Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression

BACKGROUND

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindness without proper clinical management. The tests used to assess disease progression are susceptible to process and measurement noise. The aim of this study was to develop a methodology which accounts for the inherent noise in the data and improve significant disease progression identification.

METHODS

Longitudinal observations from the Collaborative Initial Glaucoma Treatment Study (CIGTS) were used to parameterize and validate a Kalman filter model and logistic regression function. The Kalman filter estimates the true value of biomarkers associated with OAG and forecasts future values of these variables. We develop two logistic regression models via generalized estimating equations (GEE) for calculating the probability of experiencing significant OAG progression: one model based on the raw measurements from CIGTS and another model based on the Kalman filter estimates of the CIGTS data. Receiver operating characteristic (ROC) curves and associated area under the ROC curve (AUC) estimates are calculated using cross-fold validation.

RESULTS

The logistic regression model developed using Kalman filter estimates as data input achieves higher sensitivity and specificity than the model developed using raw measurements. The mean AUC for the Kalman filter-based model is 0.961 while the mean AUC for the raw measurements model is 0.889. Hence, using the probability function generated via Kalman filter estimates and GEE for logistic regression, we are able to more accurately classify patients and instances as experiencing significant OAG progression.

CONCLUSION

A Kalman filter approach for estimating the true value of OAG biomarkers resulted in data input which improved the accuracy of a logistic regression classification model compared to a model using raw measurements as input. This methodology accounts for process and measurement noise to enable improved discrimination between progression and nonprogression in chronic diseases.

Detection of progression of glaucomatous visual field damage using the point-wise method with the binomial test

Purpose

To compare the performance of newly proposed point-wise linear regression (PLR) with the binomial test (binomial PLR) against mean deviation (MD) trend analysis and permutation analyses of PLR (PoPLR), in detecting global visual field (VF) progression in glaucoma.

Methods

15 VFs (Humphrey Field Analyzer, SITA standard, 24-2) were collected from 96 eyes of 59 open angle glaucoma patients (6.0 ± 1.5 [mean ± standard deviation] years). Using the total deviation of each point on the 2^nd to 16^th VFs (VF2-16), linear regression analysis was carried out. The numbers of VF test points with a significant trend at various probability levels (p<0.025, 0.05, 0.075 and 0.1) were investigated with the binomial test (one-side). A VF series was defined as “significant” if the median p-value from the binomial test was <0.025. Similarly, the progression analysis was carried out using only second to sixth VFs (VF2-6). The performance of each method was evaluated using the ‘consistency measures’; proportion both significant (PBS): both VF series (VF2-6 and VF2-16) were “significant”, proportion both were not significant (PBNS): both were “not significant”, proportion inconsistently significant (PIS): VF2-16 was “not significant” but VF2-6 was “significant”. A similar analysis was carried out using VF2-7 and VF2-15 series, and the performance was compared with MD trend analysis and PoPLR.

Results

The PBS of the binomial PLR method (0.14 to 0.86) was significantly higher than MD trend analysis (0.04 to 0.89) and PoPLR (0.09 to 0.93). The PIS of the proposed method (0.0 to 0.17) was significantly lower than the MD approach (0.0 to 0.67) and PoPLR (0.07 to 0.33). The PBNS of the three approaches were not significantly different.

Conclusions

The binomial BLR method gives more consistent results than MD trend analysis and PoPLR, hence it will be helpful as a tool to ‘flag’ possible VF deterioration.

Measuring visual field progression in the central 10 degrees using additional information from central 24 degrees visual fields and 'lasso regression'

Purpose

To measure progression of the visual field (VF) mean deviation (MD) index in longitudinal 10-2 VFs more accurately, by adding information from 24-2 VFs using Lasso regression.

Methods

A training dataset consisted of 138 eyes from 97 patients with glaucoma or ocular hypertension and a testing dataset consisted of 40 eyes from 34 patients with glaucoma or ocular hypertension. The Lasso method was used to predict total deviation (TD) values in training patients’ 10-2 VFs based on information from their 24-2 VFs (52 TD values, foveal sensitivity and mean deviation MD). Then, the MD of each patient’s 10-2 VF was estimated as the average of these Lasso-predicted TD values (10-2 VF ‘Lasso MD’; LMD). Finally, linear regression was applied to each testing patient’s series of longitudinal 10-2 VF MDs with and without additional Lasso-derived LMDs in order to predict future MDs not included in the regression analysis. Absolute prediction errors were compared when only actual 10-2 MDs were regressed against when a combination of actual 10-2 MDs and LMDs were regressed.

Results

The average absolute prediction error was significantly smaller for the novel method incorporating LMDs (range: 1.6 to 1.8 dB) compared with the standard approach (range: 1.7 to 3.4 dB) (p<0.05, ANOVA test).

Conclusions

Deriving 10-2 VF MD values from 24-2 VFs improves the prediction accuracy of progression. This approach will help clinicians to predict patients’ visual function in the parafoveal area.

The structure and function relationship in glaucoma: implications for detection of progression and measurement of rates of change

PURPOSE

To evaluate the relationship between change in estimated retinal ganglion cell (RGC) counts and change in measures of functional and structural damage in glaucoma, from cross-sectional data.

METHODS

The study included 397 eyes of 397 patients with glaucoma, suspects, and healthy individuals. All eyes underwent testing with standard automated perimetry (SAP) and spectral-domain optical coherence tomography (SD-OCT). Estimates of retinal ganglion cell (RGC) counts were obtained from SAP and SD-OCT using a previously derived algorithm. Smoothing spline curves were fitted to investigate the relationship between functional/structural parameters and RGC counts. The first derivatives (i.e., slopes) of these curves were obtained to investigate the relationship between changes in these measures.

RESULTS

A nonlinear relationship was observed between SAP mean deviation (MD) and RGC counts. The same amount of RGC loss corresponded to largely different amounts of MD change depending on the stage of the disease. For SDOCT average retinal nerve fiber layer (RNFL) thickness, a linear relationship was seen with RGC counts throughout most of the spectrum of disease, but reaching a plateau in advanced glaucoma. Changes in RGC counts for eyes with early damage corresponded to small changes in MD, but to relatively larger changes in RNFL thickness. For eyes with advanced disease, changes in RGC counts produced relatively larger changes in MD but only small or no changes in average RNFL thickness.

CONCLUSIONS

The analysis and interpretation of rates of SAP and SD-OCT change, as indicators of the velocity of neural damage in glaucoma, should take into account the severity of the disease.

Improved estimates of visual field progression using bayesian linear regression to integrate structural information in patients with ocular hypertension

PURPOSE

To assess whether neuroretinal rim area (RA) measurements of the optic disc could be used to improve the estimate of the rate of change in visual field (VF) mean sensitivity in patients with ocular hypertension (OHT) using a Bayesian linear regression (BLR), compared to a standard ordinary least squares linear regression (OLSLR) of mean sensitivity (MS) measurements alone.

METHODS

MS and RA measurements were analyzed from a longitudinal series of 179 patients with OHT visiting Moorfields Eye Hospital between 1992 and 2000. For each patient, linear regression of RA was computed after an appropriate transformation to "scale" RA with MS measurements, and the slope coefficient from this regression was used as a prior for BLR of MS. The BLR then was compared with the OLSLR approach by evaluating how accurately each regression technique predicted future MS measurements.

RESULTS

On average, BLR was significantly more accurate than OLSLR for series up to 8 measurements long (root-mean-square prediction error [RMSPE] was 0.14 decibels [dB] smaller with BLR than OLSLR; P < 0.001, Wilcoxon signed-rank test), with OLSLR of VF data alone being more accurate for longer series (RMSPE was 0.06 dB smaller with OLSLR than BLR).

CONCLUSIONS

BLR provides a significantly more accurate estimate of the rate of change in MS than the standard OLSLR approach, especially in short time series, suggesting that structural measurements can be used successfully in statistical models to assist clinicians monitoring VF progression in patients with OHT. Further studies are necessary to validate the method in glaucoma patients.

Incorporating life expectancy in glaucoma care

AIM

To calculate for which combinations of age and perimetric disease stage glaucoma patients are unlikely to become visually impaired during their lifetime.

METHODS

We used residual life expectancy data (life expectancy adjusted for the age already reached) as provided by Statistics Netherlands and rates of progression as derived from published studies. We calculated the baseline mean deviation (MD) for which an individual would reach a MD of -20 dB at the end of life as a function of age and rate of progression. For situations in which the individual rate of progression is unknown, we used the 90th percentiles of rate of progression and residual life expectancy. For situations in which the individual rate of progression is known, we used the 95th percentile of the residual life expectancy.

RESULTS

An easily applicable graphical tool was developed that enables an accurate estimate of the probability of becoming visually impaired during lifetime, given age, current glaucomatous damage, and--if available--the individual rate of progression.

CONCLUSIONS

This novel tool enables the clinician to incorporate life expectancy in glaucoma care in a well-founded manner and may serve as a starting point for personalized decision making.

Event-based progression detection strategies using scanning laser polarimetry images of the human retina

Monitoring glaucoma patients and ensuring optimal treatment requires accurate and precise detection of progression. Many glaucomatous progression detection strategies may be formulated for Scanning Laser Polarimetry (SLP) data of the local nerve fiber thickness. In this paper, several strategies, all based on repeated GDx VCC SLP measurements, are tested to identify the optimal one for clinical use. The parameters of the methods were adapted to yield a set specificity of 97.5% on real image series. For a fixed sensitivity of 90%, the minimally detectable loss was subsequently determined for both localized and diffuse loss. Due to the large size of the required data set, a previously described simulation method was used for assessing the minimally detectable loss. The optimal strategy was identified and was based on two baseline visits and two follow-up visits, requiring two-out-of-four positive tests. Its associated minimally detectable loss was 5-12 μm, depending on the reproducibility of the measurements.

A critical discussion of the rates of progression and causes of optic nerve damage in glaucoma: International Glaucoma Think Tank II: July 25-26, 2008, Florence, Italy

The International Glaucoma Think Tank II brought together glaucoma clinicians and researchers from all over the world to discuss current practices in glaucoma diagnosis and management, and the neurobiology of glaucoma. The meeting focused on several themes, including rates of deterioration in glaucoma patients, mechanisms of optic nerve damage, and implications for treatment. Issues such as how to measure and integrate progression information into clinical practice, screening protocols, or trials were discussed, as were promising new technologies and limitations of currently available measurement tools. Clinical applications for genetic testing were considered. Study of the neurobiology of glaucoma continues to inform our understanding of underlying degenerative processes, as well as to introduce possibilities for early detection or prevention. Many questions regarding glaucoma pathophysiology and best treatment practices remain unanswered, but with continued research and discussion, we will advance our understanding of this disease and ensure that patients receive optimal care.

Glaucoma: an area of darkness

This review of Primary Open Angle Glaucoma looks at the management of the condition today. It does this by looking at the following areas: (a) the size of the problem; (b) the position of IOP, with respect to its elevation and fluctuation; (c) optic nerve head changes; and (d) visual function changes. In doing so, it contrasts what is known now with ideas and concepts that were prevalent at the time of the two previous Bowman lecturers, Duke Elder and Drance, as well as noting concepts about the disease that were current at the time of William Bowman. The review concludes by suggesting challenges in this area that lie ahead.

A visual field index for calculation of glaucoma rate of progression

PURPOSE

To present a new perimetric index for calculating the rate of glaucomatous progression and to compare its performance with the traditional mean deviation index (MDI).

DESIGN

Experimental study describing a device and retrospective cohort study.

METHODS

We developed a new visual field index, the glaucoma progression index (GPI), intended to be less affected by cataract than the MDI by calculating age-corrected defect depth at test points identified as significantly depressed in pattern deviation probability maps. The valid operating range for pattern deviation analysis was estimated. When exceeding this range, the total deviation probability maps were used for identification of significantly depressed points. The GPI is expressed in percentage, where 100% represents a normal visual field and 0% represents a perimetrically blind field, and is plotted vs patient age. Rate of progression, presented as yearly change in the GPI, is calculated by linear regression analysis. We conducted a pilot evaluation in three groups of patients: 1) eyes with developing cataract, 2) eyes without cataract, and 3) eyes in which cataract surgery was performed in the middle of the series.

RESULTS

The cut-off for pattern deviation was, at mean deviation, worse than -20 decibels (dB) in fields in which the eighty-fifth percentile of the total deviation value was significantly depressed. In the first group (n = 45), the measured rate of progression was greater with the MDI than with the GPI (P < .0001). The mean loss per year was 3.6%/year for the MDI and 2.1%/year for the GPI. In the second group (n = 42), the rate of progression did not differ between the MDI and the GPI (P = .52); the means were 2.7%/year and 2.6%/year, respectively. In the third group (n = 44), the confidence limits for the rate of progression were significantly smaller with the GPI than with the MDI (P = .04).

CONCLUSIONS

Glaucoma progression rates calculated using the GPI seem to be considerably less affected by cataract and cataract surgery than rates based on the traditional MDI.

Progression detection in glaucoma can be made more efficient by using a variable interval between successive visual field tests

BACKGROUND

This study aimed to gain insight into the optimal spacing in time for visual field tests for progression detection in glaucoma.

METHODS

Three perimetric strategies for progression detection were compared by means of simulation experiments in a theoretical cohort. In strategies 1 and 2, visual field testing was performed with fixed-spaced inter-test intervals, using intervals of 3 and 6 months respectively. In strategy 3, the inter-test interval was kept at 1 year as long as the fields appeared unchanged. Then, as soon as progression was suspected, confirmation or falsification were performed promptly. Follow-up fields were compared against a baseline assuming linear deterioration, using various progression criteria. Outcome measures were: (1) specificity, (2) time delay until the diagnosis of definite progression, and (3) number of required tests.

RESULTS

Strategies 2 and 3 had a higher specificity than strategy 1. Strategies 1 and 3 detected progression earlier than strategy 2. The number of required visual field tests was lowest for strategy 3.

CONCLUSION

Perimetry in glaucoma can be optimised by postponing the next test under apparently stable field conditions and bringing the next test forward once progression is suspected.

Development and validation of a computerized expert system for evaluation of automated visual fields from the Ischemic Optic Neuropathy Decompression Trial

Background

The objective of this report is to describe the methods used to develop and validate a computerized system to analyze Humphrey visual fields obtained from patients with non-arteritic anterior ischemic optic neuropathy (NAION) and enrolled in the Ischemic Optic Neuropathy Decompression Trial (IONDT). The IONDT was a multicenter study that included randomized and non-randomized patients with newly diagnosed NAION in the study eye. At baseline, randomized eyes had visual acuity of 20/64 or worse and non-randomized eyes had visual acuity of better than 20/64 or were associated with patients refusing randomization. Visual fields were measured before treatment using the Humphrey Field Analyzer with the 24-2 program, foveal threshold, and size III stimulus.

Methods

We used visual fields from 189 non-IONDT eyes with NAION to develop the computerized classification system. Six neuro-ophthalmologists ("expert panel") described definitions for visual field patterns defects using 19 visual fields representing a range of pattern defect types. The expert panel then used 120 visual fields, classified using these definitions, to refine the rules, generating revised definitions for 13 visual field pattern defects and 3 levels of severity. These definitions were incorporated into a rule-based computerized classification system run on Excel^® software. The computerized classification system was used to categorize visual field defects for an additional 95 NAION visual fields, and the expert panel was asked to independently classify the new fields and subsequently whether they agreed with the computer classification. To account for test variability over time, we derived an adjustment factor from the pooled short term fluctuation. We examined change in defects with and without adjustment in visual fields of study participants who demonstrated a visual acuity decrease within 30 days of NAION onset (progressive NAION).

Results

Despite an agreed upon set of rules, there was not good agreement among the expert panel when their independent visual classifications were compared. A majority did concur with the computer classification for 91 of 95 visual fields. Remaining classification discrepancies could not be resolved without modifying existing definitions.

Without using the adjustment factor, visual fields of 63.6% (14/22) patients with progressive NAION and no central defect, and all (7/7) patients with a paracentral defect, worsened within 30 days of NAION onset. After applying the adjustment factor, the visual fields of the same patients with no initial central defect and 5/7 of the patients with a paracentral defect were seen to worsen.

Conclusion

The IONDT developed a rule-based computerized system that consistently defines pattern and severity of visual fields of NAION patients for use in a research setting.

Randomised controlled trial comparing the effect of brimonidine and timolol on visual field loss after acute primary angle closure

AIM

To compare the effect of brimonidine and timolol in reducing visual field loss in patients with acute primary angle closure (APAC).

METHODS

In addition to standard acute medical treatment, patients presenting with APAC were randomised to either brimonidine 0.2% or timolol 0.5% upon diagnosis, then twice daily for 4 weeks. After laser peripheral iridotomy (LPI), subjects underwent three baseline perimetry tests during the first week, and then at weeks 4, 8, 12, and 16. Pointwise linear regression analysis was applied to the field series of each of these subjects starting with the third test (total of five tests per subject). Progression was defined as a significant regression slope (p<0.05) showing 1 dB per year or more of sensitivity loss at the same test location in the series. Patients were also compared for prevalence of abnormal fields at 16 weeks, which was defined as an abnormal glaucoma hemifield test result and/or corrected pattern standard deviation outside the 95% confidence limits.

RESULTS

59 subjects (31 in the brimonidine group; 28 in the timolol group) completed the study. There were 47 females (79.7%), the majority of subjects (94.9%) were Chinese and the mean age was 59.2 (SD 7.2) years. There were no significant differences between the two groups with respect to demographic features, presenting intraocular pressure (IOP), duration of symptoms, time from presentation to LPI, or mean IOP at each study visit. Over the 16 week study period, despite adequate statistical power, no difference was found between groups in terms of the number of patients with progressing locations, the mean number of progressing locations per subject, or the mean slope of the progressing locations. Nine (29%) subjects in the brimonidine group and 10 (35.7%) in the timolol group were found to have significant visual field defects at 16 weeks (p = 0.58). 15 out of these 19 subjects (78.9%) already had these visual field defects in the first week.

CONCLUSIONS

In the first 16 weeks after APAC, there was no difference in the prevalence of visual field defects or rate of visual field progression between brimonidine and timolol treated groups.

Interobserver agreement on visual field progression in glaucoma: a comparison of methods

AIM

To examine the level of agreement between clinicians in assessing progressive deterioration in visual field series using two different methods of analysis.

METHODS

Each visual field series satisfied the following criteria: more than 19 reliable fields, patient age over 40 years, macular threshold at least 30 dB. The first three fields in each series were excluded to minimise learning effects: the following 16 were studied. Five expert clinicians assessed the progression status of each series using both standard Humphrey printouts and pointwise linear regression (PROGRESSOR). The level of agreement between the clinicians was evaluated using a weighted kappa statistic.

RESULTS

A total of 432 tests comprising 27 visual field series of 16 tests each were assessed by the clinicians. The level of agreement on progression status between the clinicians was always higher when they used PROGRESSOR (median kappa = 0.59) than when they used Humphrey printouts (median kappa = 0.32). This was statistically significant (p = 0.006, Wilcoxon matched pairs signed rank sum test).

CONCLUSIONS

Agreement between expert clinicians about visual field progression status is poor when standard Humphrey printouts are used, even when the field series studied are long and consist solely of reliable fields. Under these ideal conditions, clinicians agree more closely about patients' visual field progression status when using PROGRESSOR than when inspecting series of Humphrey printouts.

Frequency of testing for detecting visual field progression

AIMS

To investigate the effect of frequency of testing on the determination of visual field progression using pointwise linear regression (PLR).

METHODS

A "virtual eye" was developed to simulate series of sensitivities over time at a given point in the eye. The user can input the actual behaviour of the point (for example, stable or deteriorating steadily), and then a configurable amount of noise is added to produce a realistic series over time. The advantage of this over using patient data is that the actual status of the eye is known. Series were generated using different frequencies of testing, and the diagnosis that would have been made from each series was compared with the true status of the eye. A point was diagnosed as progressing if the regression line for the series showed a deterioration of at least 1 dB per year, significant at the 1% level. From these results, graphs were produced showing the number of points correctly or incorrectly diagnosed as progressing.

RESULTS

With the virtual eye deteriorating at a rate of 2 dB/year, it was found that the point was determined to be progressing quicker when more tests were carried out each year. With a stable virtual eye, it was found that increasing the frequency of testing increased the number of series that were falsely labelled as progressing during the first 3 years of testing.

CONCLUSIONS

As the frequency of testing increases, the sensitivity of PLR increases. However, the specificity decreases; possibly meaning more unnecessary changes in treatment. Three tests per year provide a good compromise between sensitivity and specificity.

Identification of progressive glaucomatous visual field loss

In normal individuals, visual field measures are not perfectly repeatable and individual test locations exhibit both short- and long-term sensitivity variations. This physiologic variability is greatly increased in glaucoma and confounds detection of real progressive loss in visual function. Distinguishing progressive glaucomatous visual field loss from test variability therefore represents a complex task. Procedures used for detection of glaucomatous visual field progression may be broadly grouped into four categories: 1) clinical judgment, which consists of simple subjective observation of sequential visual field test results; 2) defect classification systems, whereby specific criteria are used to stratify field loss by discrete score and define progression as score change over time, such as the Advanced Glaucoma Intervention Study scoring system; 3) trend analyses, which follow test parameters sequentially over time to determine the magnitude and significance of patterns within the data, for example linear regression; and 4) event analyses, which identify single events of significant change relative to a reference examination. All of these methods demonstrate distinct benefits and drawbacks, making each useful in specific circumstances, although no single method appears universally ideal. At the present time the best method of detection of progression may be to rely upon confirmation of change at successive examinations and also by correlation of visual field changes with other clinical observations. Alternative analysis methods may become available in the near future to help identify cases of progressive loss.

Sensitivity differences between real-patient and computer-stimulated visual fields

PURPOSE

The authors sought to verify computer simulation of visual fields by comparing thresholds of real and corresponding simulated visual fields.

METHODS

Four patients with stable glaucomatous visual fields and three patients with progressing glaucomatous visual fields were chosen for the study. Visual fields had been recorded at 6-month intervals for 5 to 7.5 years. A previously described computer simulation program was used to generate a corresponding simulated visual field for each of the real fields. Twenty different levels of response variability and long-term variability were used in the simulations. Pointwise sensitivity differences between real and simulated fields were calculated. The average difference and 95% interval of the differences were analyzed for the different simulation conditions, for the pointwise sensitivities in the real patient fields, and to determine whether the field was stable or progressing.

RESULTS

In almost all simulation conditions, the average pointwise sensitivity differences ranged from -1 to 1 dB and were not significantly different among different simulation conditions. The 95% interval of the average difference increased significantly with response variability, whereas long-term variability failed to show any apparent effect. Average pointwise differences and the 95% intervals were greatest in locations where the real-patient field had reduced sensitivity of 14 dB or worse.

CONCLUSION

The simulation program provided good estimates of visual field sensitivities. Increasing amounts of response, but not long-term variability, produced a linear increase in the variability of threshold sensitivities. This finding implies that short-term rather than long-term fluctuation is the most important factor determining the variability of thresholds.

Glaucoma surgery with or without adjunctive antiproliferatives in normal tension glaucoma: 2 Visual field progression

BACKGROUND

Reduction of intraocular pressure by 20-30% with glaucoma drainage surgery slows disease progression in normal tension glaucoma (NTG). It is not clear whether adjunctive antiproliferative agents are necessary or safe in eyes at low risk for scarring.

METHOD

61 eyes of 61 white patients with NTG who had undergone a primary guarded fistulising procedure were reviewed. 20 eyes had no antiproliferatives (nil), 29 had peroperative 5-fluorouracil (5-FU), and 12 had peroperative mitomycin C (MMC). Pointwise linear regression analysis (PROGRESSOR for Windows software) was applied to their visual field series starting with the first visual field following surgery and adding subsequent visual fields one at a time. Progression of visual field loss was defined as the appearance of a regression slope 1 dB per year or more with a significance of p<0.01 at one or more visual field locations which remained consistent with the addition of two of three successive visual fields. Time updated covariate analysis was used to determine the relation between variables that changed with time, such as IOP, and the risk of progression.

RESULTS

The median percentage IOP reduction was 24.4 for the nil group, 38.0 for the 5-FU group, and 47.5 for the MMC group (p=0.001). There was a statistically significant relation between percentage change in IOP and risk of visual field progression in the subsequent 6 month period for all patients analysed as one group, hazard ratio = -0.021 (p=0.002). There was a statistically significantly increase in the risk of visual field progression for the MMC group compared with the 5-FU group, hazard ratio = 1.51 (p=0.02).

CONCLUSION

In NTG patients, the IOP reduction produced by drainage surgery reduces the risk that visual field progression may be reduced after drainage surgery; this is related to the level of IOP reduction. The percentage drop in IOP during a given time is related to the risk of subsequent visual field progression. However, the use of MMC is associated with a greater risk of visual field progression despite a greater fall in IOP. This visual field deterioration may be related to the functional loss produced by late postoperative complications which have been reported at a higher rate in this group. The use of adjunctive perioperative 5-FU should maintain a suitable target IOP with preservation of visual function without the additional complications and associated visual deterioration seen with adjunctive MMC.

Comparison of visual field progression in patients with normal pressure glaucoma between eyes with and without visual field loss that threatens fixation

AIM

To compare the frequency and site of visual field progression and changes in visual acuity in patients with normal pressure glaucoma (NPG) with and without pre-existing visual field loss.

METHOD

Patients with normal tension glaucoma were selected who had at least 10 visual fields over 5 or more years of follow up and no other condition that might influence the visual field or visual acuity. Alternate left and right eyes were selected from patients in random order. These eyes were then subdivided according to visual field defect threatening fixation, visual field defect not threatening fixation, and no visual field defect (fellow eyes). Eyes were defined as showing a threat to fixation according to the presence of a visual field defect involving one of more of four paracentral visual field locations. Pointwise linear regression analysis was applied to each visual field series using PROGRESSOR software. Progression of visual field loss was defined as the appearance of a regression slope 1 dB per year or more with a significance of p<0.01, which remained consistent with the addition of two of three successive visual fields to the series. The number of patients showing progression and the number where progression occurred in one of the four paracentral visual field locations was noted. The number of eyes losing two or more lines of Snellen visual acuity over the follow up period was also noted.

RESULTS

174 eyes of 174 patients were selected. 106 eyes had visual field loss threatening fixation, 46 eyes had visual field loss that did not threaten fixation, and 22 were fellow eyes with normal visual fields. The median follow up was 7.2 years. Eight eyes (36.4%) in the "normal visual fields" group, 31 eyes (67.4%) in the "visual field loss away from fixation" group, and 87 eyes (82.1%) in the "threat to fixation" group showed progression in any part of the visual field. Two eyes (9.1%) in the "normal visual fields" group, nine eyes (19.6%) in the "visual field loss away from fixation" group, and 45 eyes (42.5%) in the "threat to fixation" group showed progression at "threat to fixation". The Cox proportional hazards regression model showed an increased risk of progression at any part of the visual field for female sex and a decreased risk for eyes with normal visual fields. For progression at threat to fixation this model showed an increased risk with pre-existing threat to fixation. Eyes from older patients and those that went on to have progressive visual field loss at fixation were more likely to lose two lines of Snellen visual acuity over the follow up period.

CONCLUSION

Since 20-30% of previously field damaged eyes and over 60% without prior field loss fail to demonstrate progressive visual field damage over a long follow up it is recommended that normal pressure glaucoma patients be monitored for progression and that potentially harmful therapy be withheld until progression is demonstrated. Although the presence of visual field loss that threatens fixation does not constitute an increased risk of visual field progression it does indicate an increased risk of further loss of visual field close to fixation which is in turn associated with loss of central acuity. In the light of this finding, patients with visual field loss that threatens fixation should be managed more aggressively.