Christiaan Wesselink

Factors That Influence Standard Automated Perimetry Test Results in Glaucoma: Test Reliability, Technician Experience, Time of Day, and Season

PURPOSE To determine the influence of several factors on standard automated perimetry test results in glaucoma. METHODS Longitudinal Humphrey field analyzer 30-2 Swedish interactive threshold algorithm data from 160 eyes of 160 glaucoma patients were used. The influence of technician experience, time of day, and season on the mean deviation (MD) was determined by performing linear regression analysis of MD against time on a series of visual fields and subsequently performing a multiple linear regression analysis with the MD residuals as dependent variable and the factors mentioned above as independent variables. Analyses were performed with and without adjustment for the test reliability (fixation losses and false-positive and false-negative answers) and with and without stratification according to disease stage (baseline MD). RESULTS Mean follow-up was 9.4 years, with on average 10.8 tests per patient. Technician experience, time of day, and season were associated with the MD. Approximately 0.2 dB lower MD values were found for inexperienced technicians (P < 0.001), tests performed after lunch (P < 0.001), and tests performed in the summer or autumn (P < 0.001). The effects of time of day and season appeared to depend on disease stage. Independent of these effects, the percentage of false-positive answers strongly influenced the MD with a 1 dB increase in MD per 10% increase in false-positive answers. CONCLUSIONS Technician experience, time of day, season, and the percentage of false-positive answers have a significant influence on the MD of standard automated perimetry.

Incorporating life expectancy in glaucoma care

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

Risk Factors for Visual Field Progression in the Groningen Longitudinal Glaucoma Study: A Comparison of Different Statistical Approaches

PurposeTo identify risk factors for visual field progression in glaucoma and to compare different statistical approaches with this risk factor analysis. Patients and MethodsWe included 221 eyes of 221 patients. Progression was analyzed using Nonparametric Progression Analysis applied to Humphrey Field Analyzer data. Risk factors were analyzed using the statistical approaches from the Advanced Glaucoma Intervention Study, the Early Manifest Glaucoma Trial, and the Canadian Glaucoma Study. Four intraocular pressure (IOP) variables (baseline IOP, mean IOP during follow-up, IOP fluctuation, and pretreatment IOP) and 8 other risk factors were investigated. ResultsOn average, 7.1 reliable fields were available after a mean follow-up of 5.3 years; 89 eyes progressed. With the Advanced Glaucoma Intervention Study approach, age [odds ratio (OR) 1.03/y; 95% confidence interval (CI), 1.00-1.06; P=0.044] predicted progression. With an additional stepwise selection procedure, mean IOP during follow-up (OR=1.16 per mm Hg; 95% CI, 1.05-1.29; P=0.003), baseline Humphrey Field Analyzer mean deviation (MD; 2.72 for better versus worse than –6 dB; 95% CI, 1.50-4.95; P=0.001), and age (OR=1.03; 95% CI, 1.01-1.06; P=0.010) predicted progression. With the Early Manifest Glaucoma Trial approach, baseline IOP [hazard ratio (HR) 1.07; 95% CI, 1.02-1.11; P=0.010], baseline Frequency Doubling Perimeter MD (HR=1.75; 95% CI, 1.14-2.70; P=0.013), and age (HR=1.03; 95% CI, 1.01-1.05; P=0.006) predicted progression. Finally, with the Canadian Glaucoma Study approach, baseline IOP (HR=1.07; 95% CI, 1.02-1.11; P=0.010), baseline Frequency Doubling Perimeter MD (HR=1.75; 95% CI, 1.14-2.70; P=0.013), and age (HR=1.03; 95% CI, 1.01-1.05; P=0.006) predicted progression. ConclusionsIOP, disease stage, and age seemed to be robust independent risk factors for visual field progression in glaucoma. The IOP variable that was significant depended on the statistical approach applied.

Persistence, Spatial Distribution and Implications for Progression Detection of Blind Parts of the Visual Field in Glaucoma: A Clinical Cohort Study

Background Visual field testing is an essential part of glaucoma care. It is hampered by variability related to the disease itself, response errors and fatigue. In glaucoma, blind parts of the visual field contribute to the diagnosis but - once established – not to progression detection; they only increase testing time. The aims of this study were to describe the persistence and spatial distribution of blind test locations in standard automated perimetry in glaucoma and to explore how the omission of presumed blind test locations would affect progression detection. Methodology/Principal Findings Data from 221 eyes of 221 patients from a cohort study with the Humphrey Field Analyzer with 30–2 grid were used. Patients were stratified according to baseline mean deviation (MD) in six strata of 5 dB width each. For one, two, three and four consecutive <0 dB sensitivities in the same test location in a series of baseline tests, the median probabilities to observe <0 dB again in the concerning test location in a follow-up test were 76, 86, 88 and 90%, respectively. For <10 dB, the probabilities were 88, 95, 97 and 98%, respectively. Median (interquartile range) percentages of test locations with three consecutive <0 dB sensitivities were 0(0–0), 0(0–2), 4(0–9), 17(8–27), 27(20–40) and 60(50–70)% for the six MD strata. Similar percentages were found for a subset of test locations within 10 degree eccentricity (P>0.1 for all strata). Omitting test locations with three consecutive <0 dB sensitivities at baseline did not affect the performance of the MD-based Nonparametric Progression Analysis progression detection algorithm. Conclusions/Significance Test locations that have been shown to be reproducibly blind tend to display a reasonable blindness persistence and do no longer contribute to progression detection. There is no clinically useful universal MD cut-off value beyond which testing can be limited to 10 degree eccentricity.

Glaucoma progression detection with frequency doubling technology (FDT) compared to standard automated perimetry (SAP) in the Groningen Longitudinal Glaucoma Study

To determine the usefulness of frequency doubling perimetry (FDT) for progression detection in glaucoma, compared to standard automated perimetry (SAP).