Interobserver Agreement and Intraobserver Reproducibility of the Subjective Determination of Glaucomatous Visual Field Progression

Tanna, Angelo P.; Bandi, Jagadeesh; Budenz, Donald L.; Feuer, William J.; Feldman, Robert M.; Herndon, Leon W.; Rhee, Douglas J.; Vos, Julia Whiteside-de

doi:10.1016/j.ophtha.2010.04.038

Cited by 39 publications

(39 citation statements)

References 14 publications

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“…The data from this reading were used to determine intra-observer reproducibility, the subject of another report, 14 and are not included in this manuscript. Then, four months after round 1 of expert review, the overview printouts and GPA printouts of the same visual field series were sent to the readers for additional assessment (in the current study, this is referred to as round 2 of expert review).…”

Section: Methodsmentioning

confidence: 99%

Glaucoma Progression Analysis Software Compared with Expert Consensus Opinion in the Detection of Visual Field Progression in Glaucoma

et al. 2012

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Purpose To compare the results of Glaucoma Progression Analysis (GPA, Carl Zeiss Meditec, Dublin, CA) to subjective expert consensus in the detection of glaucomatous visual field progression. Design Retrospective, observational case series. Participants 100 eyes of 83 glaucoma patients. Methods Five serial Humphrey visual fields from 100 eyes of 83 glaucoma patients were evaluated by five masked glaucoma subspecialists for determination of progression. Four months later, with a randomly reordered patient sequence, the same visual field series were re-evaluated by the same graders, at which time they had access to the Glaucoma Progression Analysis (GPA) printout. Main Outcome Measures The level of agreement between majority expert consensus and GPA, both before and after access to GPA data, was assessed using kappa statistics. Results On initial review and on re-evaluation with access to the GPA printout, the level of agreement between majority expert consensus and GPA was fair (kappa = 0.52, 95% confidence interval [CI] = 0.35 – 0.69 and 0.62, 95% CI = 0.46 – 0.78, respectively). Expert consensus was more likely to classify a series of fields as showing progression than was GPA (p ≤ 0.002). There was good agreement between expert consensus on initial review and reevaluation 4 months later (kappa = 0.77, 95% CI = 0.65 – 0.90). Conclusions The level of agreement between majority expert consensus of subjective determination of visual field progression and GPA is fair. In cases of disagreement with GPA, the expert consensus classification was usually progression. Access to the results of GPA did not significantly change the level of agreement between expert consensus and the GPA result; however, expert consensus did change in 11 of 100 cases.

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Section: Methodsmentioning

confidence: 99%

Glaucoma Progression Analysis Software Compared with Expert Consensus Opinion in the Detection of Visual Field Progression in Glaucoma

et al. 2012

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“…Glaucoma stability on treatment is assessed by monitoring the visual field with SAP tests, repeated at intervals of between 2 months and 2 years over a patient's lifetime. Computational methods are required to analyse series of SAP data to identify change; without these, even experienced clinicians have been shown to make inconsistent decisions [12], [13]. Current statistical approaches typically use ordinary least squares regression over time to track changes in summary measures, regions of interest or individual visual field locations [14]–[17].…”

Section: Background and Significancementioning

confidence: 99%

Detecting Changes in Retinal Function: Analysis with Non-Stationary Weibull Error Regression and Spatial Enhancement (ANSWERS)

et al. 2014

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Visual fields measured with standard automated perimetry are a benchmark test for determining retinal function in ocular pathologies such as glaucoma. Their monitoring over time is crucial in detecting change in disease course and, therefore, in prompting clinical intervention and defining endpoints in clinical trials of new therapies. However, conventional change detection methods do not take into account non-stationary measurement variability or spatial correlation present in these measures. An inferential statistical model, denoted ‘Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement’ (ANSWERS), was proposed. In contrast to commonly used ordinary linear regression models, which assume normally distributed errors, ANSWERS incorporates non-stationary variability modelled as a mixture of Weibull distributions. Spatial correlation of measurements was also included into the model using a Bayesian framework. It was evaluated using a large dataset of visual field measurements acquired from electronic health records, and was compared with other widely used methods for detecting deterioration in retinal function. ANSWERS was able to detect deterioration significantly earlier than conventional methods, at matched false positive rates. Statistical sensitivity in detecting deterioration was also significantly better, especially in short time series. Furthermore, the spatial correlation utilised in ANSWERS was shown to improve the ability to detect deterioration, compared to equivalent models without spatial correlation, especially in short follow-up series. ANSWERS is a new efficient method for detecting changes in retinal function. It allows for better detection of change, more efficient endpoints and can potentially shorten the time in clinical trials for new therapies.

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“…The degree of agreement depends on the number of experts, follow-up time and the number of visual fields in each series. Tanna et al 11 and Viswanathan et al, 12 found inter-expert agreement rates of 0.45 and 0.32, respectively. The study by Viswanathan et al included 27 cases with 16 visual fields per case, evaluated by five experts; the authors concluded that a high number of visual fields per patient and long follow-up periods can hinder and complicate the detection of progression.…”

Section: Discussionmentioning

confidence: 96%

Evaluation of Visual Field Progression in Glaucoma: Quasar Regression Program and Event Analysis

Díaz-Alemán

González-Hernández

Perera-Sanz

et al. 2015

Current Eye Research

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Interobserver Agreement and Intraobserver Reproducibility of the Subjective Determination of Glaucomatous Visual Field Progression

Cited by 39 publications

References 14 publications

Glaucoma Progression Analysis Software Compared with Expert Consensus Opinion in the Detection of Visual Field Progression in Glaucoma

Glaucoma Progression Analysis Software Compared with Expert Consensus Opinion in the Detection of Visual Field Progression in Glaucoma

Detecting Changes in Retinal Function: Analysis with Non-Stationary Weibull Error Regression and Spatial Enhancement (ANSWERS)

Evaluation of Visual Field Progression in Glaucoma: Quasar Regression Program and Event Analysis

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