A New Way to Predict and Monitor Progression in Glaucoma

Lyne Racette, PhD
Indiana University School of Medicine (Indianapolis, IN)
Year Awarded:
Grant Duration:
July 1, 2014 to December 31, 2016
Award Amount:
Grant Reference ID:
Award Type:
Award Region:
US Midwestern
Lyne Racette, PhD

An Individualized Model to Predict and Monitor Glaucoma Progression Using Structural and Functional Data


Glaucoma is an eye disease that can lead to blindness. We propose a new model to detect glaucoma changes over time. This model will be tailored for each patient and tested in a different group of patients. We will use this model to predict which patients’ glaucoma is likely to progress—or get worse—over time.


The objective of this project is to validate the performance of a new model designed to monitor glaucoma progression. This model uses structural and functional data jointly and updates its predictions and determinations with each new pair of data that becomes available. The predictive accuracy of the model is better than that obtained with ordinary least square linear regression, particularly in short follow-up series.

The first aim of this project is to validate the model in a cohort independent from the original sample that was used to develop it. Thus, our laboratory will use the large cohort enrolled in the longitudinal Ocular Hypertension Treatment Study (OHTS) to test and optimize the model.

The second aim is to estimate the sensitivity and the specificity of the model using data from two longitudinal studies: the Diagnostic Innovations in Glaucoma Study (DIGS) and the African Descent and Glaucoma Evaluation Study (ADAGES). The ability of the model to tease out true progression from variability is being assessed by comparing its determination of progression to that of other clinically accepted structural and functional measures of progression. My laboratory is developing individualized methods to improve the detection of glaucoma progression.

The present study is innovative in that it makes use of both structural and functional data to monitor glaucoma progression. The model is unique in that it makes no assumptions about how glaucoma progresses or about the nature of the relationship between structure and function. The model is also individualized, which is important given the large variability observed between patients, and offers an intuitive graphical representation of the progression status of each patient. At the conclusion of this study, clinicians will have a powerful method to monitor glaucoma progression and to identify those patients who are likely to progress. This will improve patient care and lead to the preservation of sight in glaucoma patients. The model proposed in this study is also highly relevant to assess the effectiveness of new treatments designed to slow or halt the progression of glaucoma.

About the Researcher

Lyne Racette is an assistant professor of ophthalmology at the Eugene and Marilyn Glick Eye Institute at Indiana University’s School of Medicine (Indianapolis, IN), and an adjunct professor at Indiana University’s School of Optometry (Bloomington, IN). After receiving her PhD from Carleton University (Ottawa, Canada), Dr. Racette joined the University of California at San Diego (San Diego, CA) where she completed a postdoctoral fellowship at the Hamilton Glaucoma Center. Dr. Racette’s research focuses on developing methods to improve the detection of glaucoma progression and on identifying those patients who are most at risk of experiencing vision loss. Structural and functional data are used jointly within an individualized framework to tease out true glaucomatous progression from other variables.
Don't miss out.
Receive research updates, inspiring stories, and expert advice
Please enter your first name.
Please enter your last name.
Keep me informed about: *
Please select at least one.
You must select at least one disease category.