The fundamental goal of glaucoma management is to prevent patients from developing visual impairment that is sufficient to produce disability in their daily lives and impair their health-related quality of life (HRQOL). The overall goal of the Diagnostic Innovations in Glaucoma Study (DIGS): Functional Impairment is to improve understanding of functional disability in glaucoma and how it relates to commonly performed clinical tests. This proposal will obtain measures of functional impairment in a well-defined cohort of glaucoma patients that has been followed for over 15 years with a very large variety of clinical functional and structural tests. Cross-sectional and longitudinal investigations will address the following 3 specific aims: 1) to objectively evaluate functional impairment in glaucoma using performance-based tests: driving simulation and the Assessment of Disability Related to Vision (ADREV) scale, 2) to improve understanding of HRQOL deterioration in glaucoma using patient-reported outcomes and 3) to predict which patients are at risk for functional impairment and decrease in HRQOL from glaucoma.
In Specific Aim 1, we will study the relationships between performance-based measures of functional impairment and standard clinical tests for assessment of glaucomatous optic disc and retinal nerve fiber layer damage. The investigation of these relationships will help link the results obtained by conventional testing to information related to disability from the disease and, therefore, may have significant impact on how results from different clinical tests are used for decision making and as surrogate endpoints in clinical trials of glaucoma.
In Specific Aim 2, we will investigate factors that determine patients'perceptions of impairment from glaucoma by studying the longitudinal associations between subjective (HRQOL questionnaires) and objective (performance-based) measures of functional impairment and how they are related to results of clinical tests, demographic and socio-economic factors. This will identify the reasons why some aspects of impairment are more perceptible or bothersome to patients than others and may assist in the development of strategies to compensate or minimize the impact of disability in the daily lives of glaucoma patients.
In Specific Aim 3, we will evaluate the ability of baseline and longitudinal structural and functional measures in predicting which patients are at highest risk for development of functional disability. The goal is to develop predictive models that can be used for identification of patients at higher risk for functional impairment, leading to a more efficient management of glaucoma and ultimately to a reduction of disability from the disease. By evaluating measures of functional impairment and developing predictive models to identify patients at risk for disability, this proposal directly addresses the current National Eye Institute National Plan for Eye and Vision Research goal of developing diagnostic methodologies to prevent vision loss from glaucoma.

Public Health Relevance

Glaucoma is a leading cause of vision loss in the United States and worldwide, frequently resulting in significant disability and decrease in health-related quality of life. The overall goal of this proposal entitled """"""""Diagnostic Innovations in Glaucoma Study: Functional Impairment"""""""" is to improve understanding and develop methods to identify patients at risk for disability from the disease. Specifically, we will obtain measures of functional impairment in a well-defined cohort of glaucoma patients that have been followed for several years in order to 1) study the relationship between results on standard clinical tests and the ability of patients to perform activities of daily living, including driving simulation, 2) evaluate the relationship between subjective (patient-reported) and objective measures of impairment and how the association is influenced by disease severity and socio-economic variables and 3) use results of standard tests to predict which patients are at risk for functional impairment and decrease in quality of life from glaucoma.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
1R01EY021818-01
Application #
8161130
Study Section
Anterior Eye Disease Study Section (AED)
Program Officer
Everett, Donald F
Project Start
2011-09-01
Project End
2016-08-31
Budget Start
2011-09-01
Budget End
2012-08-31
Support Year
1
Fiscal Year
2011
Total Cost
$754,058
Indirect Cost
Name
University of California San Diego
Department
Ophthalmology
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Christopher, Mark; Belghith, Akram; Bowd, Christopher et al. (2018) Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs. Sci Rep 8:16685
Mundae, Rusdeep S; Zangwill, Linda M; Kabbara, Sami W et al. (2018) A Longitudinal Analysis of Peripapillary Choroidal Thinning in Healthy and Glaucoma Subjects. Am J Ophthalmol 186:89-95
Wu, Zhichao; Medeiros, Felipe A; Weinreb, Robert N et al. (2018) Performance of the 10-2 and 24-2 Visual Field Tests for Detecting Central Visual Field Abnormalities in Glaucoma. Am J Ophthalmol 196:10-17
Suh, Min Hee; Zangwill, Linda M; Manalastas, Patricia Isabel C et al. (2018) Deep-Layer Microvasculature Dropout by Optical Coherence Tomography Angiography and Microstructure of Parapapillary Atrophy. Invest Ophthalmol Vis Sci 59:1995-2004
Manalastas, Patricia I C; Zangwill, Linda M; Daga, Fabio B et al. (2018) The Association Between Macula and ONH Optical Coherence Tomography Angiography (OCT-A) Vessel Densities in Glaucoma, Glaucoma Suspect, and Healthy Eyes. J Glaucoma 27:227-232
Wu, Zhichao; Medeiros, Felipe A (2018) Development of a Visual Field Simulation Model of Longitudinal Point-Wise Sensitivity Changes From a Clinical Glaucoma Cohort. Transl Vis Sci Technol 7:22
Christopher, Mark; Belghith, Akram; Weinreb, Robert N et al. (2018) Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression. Invest Ophthalmol Vis Sci 59:2748-2756
Nakanishi, Masaki; Wang, Yu-Te; Jung, Tzyy-Ping et al. (2017) Detecting Glaucoma With a Portable Brain-Computer Interface for Objective Assessment of Visual Function Loss. JAMA Ophthalmol 135:550-557
Diniz-Filho, Alberto; Abe, Ricardo Y; Cho, Hyong Jin et al. (2017) Reply. Ophthalmology 124:e21
Bowd, Christopher; Zangwill, Linda M; Weinreb, Robert N et al. (2017) Estimating Optical Coherence Tomography Structural Measurement Floors to Improve Detection of Progression in Advanced Glaucoma. Am J Ophthalmol 175:37-44

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