The development of a decision analytic model of changes in mean deviation in people with glaucoma: the COA model.

PURPOSE: To create and validate a statistical model predicting progression of primary open-angle glaucoma (POAG) assessed by loss of visual field as measured in mean deviation (MD) using 3 landmark studies of glaucoma progression and treatment.
DESIGN: A Markov decision analytic model using patient level data described longitudinal MD changes over 7 years. PARTICIPANTS: Patient-level data from the Collaborative Initial Glaucoma Treatment Study (n = 607), the Ocular Hypertension Treatment Study (OHTS; n = 148; only those who developed POAG in the first 5 years of OHTS) and Advanced Glaucoma Intervention Study (n = 591), the COA model.
METHODS: We developed a Markov model with transition matrices stratified by current MD, age, race, and intraocular pressure categories and used a microsimulation approach to estimate change in MD over 7 years. Internal validation compared model prediction for 7 years to actual MD for COA participants. External validation used a cohort of glaucoma patients drawn from university clinical practices. MAIN OUTCOME MEASURES: Change in visual field as measured in MD in decibels (dB).
RESULTS: Regressing the actual MD against the predicted produced an R(2) of 0.68 for the right eye and 0.63 for the left. The model predicted ending MD for right eyes of 65% of participants and for 63% of left eyes within 3 dB of actual results at 7 years. In external validation the model had an R(2) of 0.79 in the right eye and 0.77 in the left at 5 years.
CONCLUSIONS: The COA model is a validated tool for clinicians, patients, and health policy makers seeking to understand longitudinal changes in MD in people with glaucoma.