The primary objective of this project is to integrate principles and methods of operations research and systems engineering with data from NEI-funded clinical trials to develop an innovative approach to personalize the care of patients with open-angle glaucoma (OAG) and ocular hypertension (OHTN) to prevent avoidable blindness and vision loss. The outcomes sought will assist clinicians by (a) producing personalized forecasts of the probability of progressing from OHTN to OAG and less severe to more advanced disease states, (b) determining the optimal timing of specific diagnostic tests to monitor for glaucomatous progression for each patient, (c) identifying those at highest risk for irreversible vision loss from OAG (i.e., ?fast progressors?), and (d) generating recommended target treatment goals of intraocular pressure (IOP). To achieve these objectives, this project integrates an understanding of glaucoma progression trajectory from NEI-funded clinical trials (including OHTS, CIGTS, and AGIS) with an individual patient's past and current test results from perimetry, tonometry and optical coherence tomography to generate personalized forecasts of glaucoma progression dynamics. Prior work by our group has shown that a preliminary forecasting tool we developed could accurately identify instances of OAG progression 57% sooner (p=0.02) and 29% more efficiently (p<0.0001), compared with the current practice for many patients of fixed 1-year intervals for patient assessment and testing. In this proposal, we look to greatly enhance the forecasting tool in several ways.
In Aim 1 we will develop, parameterize, calibrate, and validate an advanced tool using data from the OHTS trial, to forecast if a patient with OHTN will develop OAG and the timing of progression to OAG. While our sophisticated state space Kalman filtering methodology appears to perform very well on patients with moderate to severe OAG, in this aim we plan to apply this methodology to study disease progression dynamics for patients with OHTN using data from OHTS.
In Aim 2 we plan to extend the inputs to the forecasting tool beyond data from tonometry and perimetry to now also include data from structural testing including optical coherence tomography. In addition, this aim proposes to expand the output of the tool to include personalized predictions of which patients will become fast progressors, allowing clinicians to intervene before vision is irreversibly lost. In this aim, we also plan to forecast and graphically display the patient's likely OAG progression trajectory given a menu of different possible levels of IOP control, aiding the eye-care provider and patient in choosing how aggressive the treatment should be. By fulfilling the aims of this proposal, we hope to develop an advanced forecasting tool that will provide clinicians and patients with personalized, dynamically-updated, real time forecasts of OAG progression dynamics for each eye, which will greatly aid with decreasing avoidable vision loss and blindness from OAG.

Public Health Relevance

The goal of this study is to refine and enhance a forecasting tool that we have begun developing to assist eye doctors (a) by helping to identify which patients will develop glaucoma or will experience worsening of existing glaucoma, and at what pace, (b) by recommending when the patient should next be assessed for possible disease worsening, and (c) by calculating the patient's optimal intraocular pressure, a vital measurement in glaucoma that can be controlled through carefully targeted treatment. These highly accurate forecasts and recommendations, which would be extremely difficult for an eye doctor to calculate correctly using his brain power alone, are calculated using sophisticated engineering and mathematical techniques, incorporating valuable detailed information from previous and ongoing government-sponsored treatment trials and new and previously obtained data on the specific patient for whom the forecasts and recommendations are being made. This tool will greatly inform doctors' decisions on who, when, and how aggressively to treat, in a way that avoids overtreatment and unnecessary treatment but gives the patients at highest risk for blindness their best possible chance at preserving their long-term sight, thus fulfilling a critical mission of the National Eye Institute.

National Institute of Health (NIH)
National Eye Institute (NEI)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Liberman, Ellen S
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Michigan Ann Arbor
Schools of Medicine
Ann Arbor
United States
Zip Code
Lee, Yoon H; Chen, Andrew X; Varadaraj, Varshini et al. (2018) Comparison of Access to Eye Care Appointments Between Patients With Medicaid and Those With Private Health Care Insurance. JAMA Ophthalmol 136:622-629
Kazemian, Pooyan; Lavieri, Mariel S; Van Oyen, Mark P et al. (2018) Personalized Prediction of Glaucoma Progression Under Different Target Intraocular Pressure Levels Using Filtered Forecasting Methods. Ophthalmology 125:569-577
Shekhawat, Nakul S; Shtein, Roni M; Blachley, Taylor S et al. (2017) Antibiotic Prescription Fills for Acute Conjunctivitis among Enrollees in a Large United States Managed Care Network. Ophthalmology 124:1099-1107
Ehrlich, Joshua R; Wentzloff, Jeffrey N; Imami, Nauman R et al. (2017) Establishing a Regional Glaucoma Physician Collaborative to Improve Quality of Care. Am J Ophthalmol 179:145-150
Wang, Sophia Y; Andrews, Chris A; Gardner, Thomas W et al. (2017) Ophthalmic Screening Patterns Among Youths With Diabetes Enrolled in a Large US Managed Care Network. JAMA Ophthalmol 135:432-438
Elam, Angela R; Andrews, Chris; Musch, David C et al. (2017) Large Disparities in Receipt of Glaucoma Care between Enrollees in Medicaid and Those with Commercial Health Insurance. Ophthalmology 124:1442-1448